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GitHub - hpcaitech/Open-Sora: Open-Sora: Democratizing Efficient Video Production for All
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<div class="HeaderMenu-wrapper d-flex flex-column flex-self-start flex-lg-row flex-auto rounded rounded-lg-0"> <nav class="HeaderMenu-nav" aria-label="Global"> <ul class="d-lg-flex list-style-none"> <li class="HeaderMenu-item position-relative flex-wrap flex-justify-between flex-items-center d-block d-lg-flex flex-lg-nowrap flex-lg-items-center js-details-container js-header-menu-item"> <button type="button" class="HeaderMenu-link border-0 width-full width-lg-auto px-0 px-lg-2 py-lg-2 no-wrap d-flex flex-items-center flex-justify-between js-details-target" aria-expanded="false"> Product <svg opacity="0.5" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-down HeaderMenu-icon ml-1"> <path d="M12.78 5.22a.749.749 0 0 1 0 1.06l-4.25 4.25a.749.749 0 0 1-1.06 0L3.22 6.28a.749.749 0 1 1 1.06-1.06L8 8.939l3.72-3.719a.749.749 0 0 1 1.06 0Z"></path> </svg> </button> <div class="HeaderMenu-dropdown dropdown-menu 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0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 12.25v-8.5C2 2.784 2.784 2 3.75 2Zm6.854-1h4.146a.25.25 0 0 1 .25.25v4.146a.25.25 0 0 1-.427.177L13.03 4.03 9.28 7.78a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042l3.75-3.75-1.543-1.543A.25.25 0 0 1 10.604 1Z"></path> </svg> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary Link--external" target="_blank" data-analytics-event="{"location":"navbar","action":"github_skills","context":"product","tag":"link","label":"github_skills_link_product_navbar"}" href="https://skills.github.com"> GitHub Skills <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link-external HeaderMenu-external-icon color-fg-subtle"> <path d="M3.75 2h3.5a.75.75 0 0 1 0 1.5h-3.5a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h8.5a.25.25 0 0 0 .25-.25v-3.5a.75.75 0 0 1 1.5 0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 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100%;\"\u003e\u003c/a\u003e\n \u003ca href=\"https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/WeChat.png\" rel=\"nofollow\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/ce33304a9340ae787c7cda8d19b6f3a343872353b0477771508e64a145c95fa3/68747470733a2f2f696d672e736869656c64732e696f2f62616467652fe5beaee4bfa12de5b08fe58aa9e6898be58aa0e7bea42d677265656e3f6c6f676f3d77656368617426\" data-canonical-src=\"https://img.shields.io/badge/微信-小助手加群-green?logo=wechat\u0026amp;\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\n\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eOpen-Sora: Democratizing Efficient Video Production for All\u003c/h2\u003e\u003ca id=\"user-content-open-sora-democratizing-efficient-video-production-for-all\" class=\"anchor\" aria-label=\"Permalink: Open-Sora: Democratizing Efficient Video Production for All\" href=\"#open-sora-democratizing-efficient-video-production-for-all\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eWe design and implement \u003cstrong\u003eOpen-Sora\u003c/strong\u003e, an initiative dedicated to \u003cstrong\u003eefficiently\u003c/strong\u003e producing high-quality video. We hope to make the model,\ntools and all details accessible to all. By embracing \u003cstrong\u003eopen-source\u003c/strong\u003e principles,\nOpen-Sora not only democratizes access to advanced video generation techniques, but also offers a\nstreamlined and user-friendly platform that simplifies the complexities of video generation.\nWith Open-Sora, our goal is to foster innovation, creativity, and inclusivity within the field of content creation.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e🎬 For a professional AI video-generation product, try \u003ca href=\"https://video-ocean.com/\" rel=\"nofollow\"\u003eVideo Ocean\u003c/a\u003e — powered by a superior model.\u003c/p\u003e\n\u003cdiv align=\"center\" dir=\"auto\"\u003e\n \u003ca href=\"https://video-ocean.com/\" rel=\"nofollow\"\u003e\n \u003cimg src=\"https://github.com/hpcaitech/public_assets/raw/main/colossalai/img/3.gif\" width=\"850\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\n \u003c/a\u003e\n\u003c/div\u003e\n\u003cdiv align=\"center\" dir=\"auto\"\u003e\n \u003ca href=\"https://hpc-ai.com/?utm_source=github\u0026amp;utm_medium=social\u0026amp;utm_campaign=promotion-opensora\" rel=\"nofollow\"\u003e\n \u003cimg src=\"https://github.com/hpcaitech/public_assets/raw/main/colossalai/img/1.gif\" width=\"850\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\n \u003c/a\u003e\n\u003c/div\u003e\n\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e📰 News\u003c/h2\u003e\u003ca id=\"user-content--news\" class=\"anchor\" aria-label=\"Permalink: 📰 News\" href=\"#-news\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003cstrong\u003e[2025.03.12]\u003c/strong\u003e 🔥 We released \u003cstrong\u003eOpen-Sora 2.0\u003c/strong\u003e (11B). 🎬 11B model achieves \u003ca href=\"#evaluation\"\u003eon-par performance\u003c/a\u003e with 11B HunyuanVideo \u0026amp; 30B Step-Video on 📐VBench \u0026amp; 📊Human Preference. 🛠️ Fully open-source: checkpoints and training codes for training with only \u003cstrong\u003e$200K\u003c/strong\u003e. \u003ca href=\"https://arxiv.org/abs/2503.09642v1\" rel=\"nofollow\"\u003e[report]\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e[2025.02.20]\u003c/strong\u003e 🔥 We released \u003cstrong\u003eOpen-Sora 1.3\u003c/strong\u003e (1B). With the upgraded VAE and Transformer architecture, the quality of our generated videos has been greatly improved 🚀. \u003ca href=\"#open-sora-13-model-weights\"\u003e[checkpoints]\u003c/a\u003e \u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/report_04.md\"\u003e[report]\u003c/a\u003e \u003ca href=\"https://huggingface.co/spaces/hpcai-tech/open-sora\" rel=\"nofollow\"\u003e[demo]\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e[2024.12.23]\u003c/strong\u003e The development cost of video generation models has saved by 50%! Open-source solutions are now available with H200 GPU vouchers. \u003ca href=\"https://company.hpc-ai.com/blog/the-development-cost-of-video-generation-models-has-saved-by-50-open-source-solutions-are-now-available-with-h200-gpu-vouchers\" rel=\"nofollow\"\u003e[blog]\u003c/a\u003e \u003ca href=\"https://github.com/hpcaitech/Open-Sora/blob/main/scripts/train.py\"\u003e[code]\u003c/a\u003e \u003ca href=\"https://colossalai.org/zh-Hans/docs/get_started/bonus/\" rel=\"nofollow\"\u003e[vouchers]\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e[2024.06.17]\u003c/strong\u003e We released \u003cstrong\u003eOpen-Sora 1.2\u003c/strong\u003e, which includes \u003cstrong\u003e3D-VAE\u003c/strong\u003e, \u003cstrong\u003erectified flow\u003c/strong\u003e, and \u003cstrong\u003escore condition\u003c/strong\u003e. The video quality is greatly improved. \u003ca href=\"#open-sora-12-model-weights\"\u003e[checkpoints]\u003c/a\u003e \u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/report_03.md\"\u003e[report]\u003c/a\u003e \u003ca href=\"https://arxiv.org/abs/2412.20404\" rel=\"nofollow\"\u003e[arxiv]\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e[2024.04.25]\u003c/strong\u003e 🤗 We released the \u003ca href=\"https://huggingface.co/spaces/hpcai-tech/open-sora\" rel=\"nofollow\"\u003eGradio demo for Open-Sora\u003c/a\u003e on Hugging Face Spaces.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e[2024.04.25]\u003c/strong\u003e We released \u003cstrong\u003eOpen-Sora 1.1\u003c/strong\u003e, which supports \u003cstrong\u003e2s~15s, 144p to 720p, any aspect ratio\u003c/strong\u003e text-to-image, \u003cstrong\u003etext-to-video, image-to-video, video-to-video, infinite time\u003c/strong\u003e generation. In addition, a full video processing pipeline is released. \u003ca href=\"#open-sora-11-model-weights\"\u003e[checkpoints]\u003c/a\u003e \u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/report_02.md\"\u003e[report]\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e[2024.03.18]\u003c/strong\u003e We released \u003cstrong\u003eOpen-Sora 1.0\u003c/strong\u003e, a fully open-source project for video generation.\nOpen-Sora 1.0 supports a full pipeline of video data preprocessing, training with\n\u003ca href=\"https://github.com/hpcaitech/ColossalAI\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/readme/colossal_ai.png\" width=\"8%\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\nacceleration,\ninference, and more. Our model can produce 2s 512x512 videos with only 3 days training. \u003ca href=\"#open-sora-10-model-weights\"\u003e[checkpoints]\u003c/a\u003e\n\u003ca href=\"https://hpc-ai.com/blog/open-sora-v1.0\" rel=\"nofollow\"\u003e[blog]\u003c/a\u003e \u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/report_01.md\"\u003e[report]\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e[2024.03.04]\u003c/strong\u003e Open-Sora provides training with 46% cost reduction.\n\u003ca href=\"https://hpc-ai.com/blog/open-sora\" rel=\"nofollow\"\u003e[blog]\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e📍 Since Open-Sora is under active development, we remain different branches for different versions. The latest version is \u003ca href=\"https://github.com/hpcaitech/Open-Sora\"\u003emain\u003c/a\u003e. Old versions include: \u003ca href=\"https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.0\"\u003ev1.0\u003c/a\u003e, \u003ca href=\"https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.1\"\u003ev1.1\u003c/a\u003e, \u003ca href=\"https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.2\"\u003ev1.2\u003c/a\u003e, \u003ca href=\"https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.3\"\u003ev1.3\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e🎥 Latest Demo\u003c/h2\u003e\u003ca id=\"user-content--latest-demo\" class=\"anchor\" aria-label=\"Permalink: 🎥 Latest Demo\" href=\"#-latest-demo\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eDemos are presented in compressed GIF format for convenience. For original quality samples and their corresponding prompts, please visit our \u003ca href=\"https://hpcaitech.github.io/Open-Sora/\" rel=\"nofollow\"\u003eGallery\u003c/a\u003e.\u003c/p\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003e5s 1024×576\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e5s 576×1024\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e5s 576×1024\u003c/strong\u003e\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/8g9y9h?autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/ft_0001_1_1.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/k50mnv?autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/movie_0160.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/bzrn9n?autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/movie_0017.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/dsv8da?autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/ft_0012_1_1.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/3wif07?autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/douyin_0005.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/us2w7h?autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/movie_0037.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/yfwk8i?autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/ft_0055_1_1.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/jgjil0?autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/sora_0019.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/lsoai1?autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/movie_0463.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cdetails\u003e\n\u003csummary\u003eOpenSora 1.3 Demo\u003c/summary\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003e5s 720×1280\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e5s 720×1280\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e5s 720×1280\u003c/strong\u003e\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/r0imrp?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_tomato.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/hfvjkh?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_fisherman.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/kutmma?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_girl2.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/osn1la?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_grape.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/l1pzws?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_mushroom.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/2vqari?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_parrot.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/1in7d6?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_trans.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/e9bi4o?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_bear.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/09z7xi?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_futureflower.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/16c3hk?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_fire.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/wi250w?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_man.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://streamable.com/e/vw5b64?quality=highest\u0026amp;autoplay=1\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_black.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003c/details\u003e\n\u003cdetails\u003e\n\u003csummary\u003eOpenSora 1.2 Demo\u003c/summary\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003e4s 720×1280\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e4s 720×1280\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e4s 720×1280\u003c/strong\u003e\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/7895aab6-ed23-488c-8486-091480c26327\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0013.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/20f07c7b-182b-4562-bbee-f1df74c86c9a\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_1718.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/3d897e0d-dc21-453a-b911-b3bda838acc2\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0087.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/644bf938-96ce-44aa-b797-b3c0b513d64c\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0052.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/272d88ac-4b4a-484d-a665-8d07431671d0\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_1719.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/ebbac621-c34e-4bb4-9543-1c34f8989764\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0002.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/a1e3a1a3-4abd-45f5-8df2-6cced69da4ca\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0011.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/d6ce9c13-28e1-4dff-9644-cc01f5f11926\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0004.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/561978f8-f1b0-4f4d-ae7b-45bec9001b4a\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0061.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003c/details\u003e\n\u003cdetails\u003e\n\u003csummary\u003eOpenSora 1.1 Demo\u003c/summary\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003e2s 240×426\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e2s 240×426\u003c/strong\u003e\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c31ebc52-de39-4a4e-9b1e-9211d45e05b2\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sample_16x240x426_9.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c31ebc52-de39-4a4e-9b1e-9211d45e05b2\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x240x426_26.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/f7ce4aaa-528f-40a8-be7a-72e61eaacbbd\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x240x426_27.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/5d58d71e-1fda-4d90-9ad3-5f2f7b75c6a9\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x240x426_40.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003e2s 426×240\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e4s 480×854\u003c/strong\u003e\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/34ecb4a0-4eef-4286-ad4c-8e3a87e5a9fd\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x426x240_24.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c1619333-25d7-42ba-a91c-18dbc1870b18\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sample_32x480x854_9.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003e16s 320×320\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e16s 224×448\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e2s 426×240\u003c/strong\u003e\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/3cab536e-9b43-4b33-8da8-a0f9cf842ff2\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sample_16s_320x320.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/9fb0b9e0-c6f4-4935-b29e-4cac10b373c4\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sample_16s_224x448.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/3e892ad2-9543-4049-b005-643a4c1bf3bf\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x426x240_3.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003c/details\u003e\n\u003cdetails\u003e\n\u003csummary\u003eOpenSora 1.0 Demo\u003c/summary\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003e2s 512×512\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e2s 512×512\u003c/strong\u003e\u003c/th\u003e\n\u003cth\u003e\u003cstrong\u003e2s 512×512\u003c/strong\u003e\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/de1963d3-b43b-4e68-a670-bb821ebb6f80\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_0.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/13f8338f-3d42-4b71-8142-d234fbd746cc\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_1.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/fa6a65a6-e32a-4d64-9a9e-eabb0ebb8c16\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_2.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eA serene night scene in a forested area. [...] The video is a time-lapse, capturing the transition from day to night, with the lake and forest serving as a constant backdrop.\u003c/td\u003e\n\u003ctd\u003eA soaring drone footage captures the majestic beauty of a coastal cliff, [...] The water gently laps at the rock base and the greenery that clings to the top of the cliff.\u003c/td\u003e\n\u003ctd\u003eThe majestic beauty of a waterfall cascading down a cliff into a serene lake. [...] The camera angle provides a bird's eye view of the waterfall.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/64232f84-1b36-4750-a6c0-3e610fa9aa94\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_3.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/983a1965-a374-41a7-a76b-c07941a6c1e9\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_4.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca href=\"https://github.com/hpcaitech/Open-Sora/assets/99191637/ec10c879-9767-4c31-865f-2e8d6cf11e65\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_5.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eA bustling city street at night, filled with the glow of car headlights and the ambient light of streetlights. [...]\u003c/td\u003e\n\u003ctd\u003eThe vibrant beauty of a sunflower field. The sunflowers are arranged in neat rows, creating a sense of order and symmetry. [...]\u003c/td\u003e\n\u003ctd\u003eA serene underwater scene featuring a sea turtle swimming through a coral reef. The turtle, with its greenish-brown shell [...]\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cp dir=\"auto\"\u003eVideos are downsampled to \u003ccode\u003e.gif\u003c/code\u003e for display. Click for original videos. Prompts are trimmed for display,\nsee \u003ca href=\"/hpcaitech/Open-Sora/blob/main/assets/texts/t2v_samples.txt\"\u003ehere\u003c/a\u003e for full prompts.\u003c/p\u003e\n\u003c/details\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e🔆 Reports\u003c/h2\u003e\u003ca id=\"user-content--reports\" class=\"anchor\" aria-label=\"Permalink: 🔆 Reports\" href=\"#-reports\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003cstrong\u003e\u003ca href=\"https://arxiv.org/abs/2503.09642v1\" rel=\"nofollow\"\u003eTech Report of Open-Sora 2.0\u003c/a\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e\u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/train.md\"\u003eStep by step to train or finetune your own model\u003c/a\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e\u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/ae.md\"\u003eStep by step to train and evaluate an video autoencoder\u003c/a\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e\u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/hcae.md\"\u003eVisit the high compression video autoencoder\u003c/a\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eReports of previous version (better see in according branch):\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/report_04.md\"\u003eOpen-Sora 1.3\u003c/a\u003e: shift-window attention, unified spatial-temporal VAE, etc.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/report_03.md\"\u003eOpen-Sora 1.2\u003c/a\u003e, \u003ca href=\"https://arxiv.org/abs/2412.20404\" rel=\"nofollow\"\u003eTech Report\u003c/a\u003e: rectified flow, 3d-VAE, score condition, evaluation, etc.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/report_02.md\"\u003eOpen-Sora 1.1\u003c/a\u003e: multi-resolution/length/aspect-ratio, image/video conditioning/editing, data preprocessing, etc.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/hpcaitech/Open-Sora/blob/main/docs/report_01.md\"\u003eOpen-Sora 1.0\u003c/a\u003e: architecture, captioning, etc.\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e📍 Since Open-Sora is under active development, we remain different branches for different versions. The latest version is \u003ca href=\"https://github.com/hpcaitech/Open-Sora\"\u003emain\u003c/a\u003e. Old versions include: \u003ca href=\"https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.0\"\u003ev1.0\u003c/a\u003e, \u003ca href=\"https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.1\"\u003ev1.1\u003c/a\u003e, \u003ca href=\"https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.2\"\u003ev1.2\u003c/a\u003e, \u003ca href=\"https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.3\"\u003ev1.3\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eQuickstart\u003c/h2\u003e\u003ca id=\"user-content-quickstart\" class=\"anchor\" aria-label=\"Permalink: Quickstart\" href=\"#quickstart\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eInstallation\u003c/h3\u003e\u003ca id=\"user-content-installation\" class=\"anchor\" aria-label=\"Permalink: Installation\" href=\"#installation\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"# create a virtual env and activate (conda as an example)\nconda create -n opensora python=3.10\nconda activate opensora\n\n# download the repo\ngit clone https://github.com/hpcaitech/Open-Sora\ncd Open-Sora\n\n# Ensure torch \u0026gt;= 2.4.0\npip install -v . # for development mode, `pip install -v -e .`\npip install xformers==0.0.27.post2 --index-url https://download.pytorch.org/whl/cu121 # install xformers according to your cuda version\npip install flash-attn --no-build-isolation\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e create a virtual env and activate (conda as an example)\u003c/span\u003e\nconda create -n opensora python=3.10\nconda activate opensora\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e download the repo\u003c/span\u003e\ngit clone https://github.com/hpcaitech/Open-Sora\n\u003cspan class=\"pl-c1\"\u003ecd\u003c/span\u003e Open-Sora\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Ensure torch \u0026gt;= 2.4.0\u003c/span\u003e\npip install -v \u003cspan class=\"pl-c1\"\u003e.\u003c/span\u003e \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e for development mode, `pip install -v -e .`\u003c/span\u003e\npip install xformers==0.0.27.post2 --index-url https://download.pytorch.org/whl/cu121 \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e install xformers according to your cuda version\u003c/span\u003e\npip install flash-attn --no-build-isolation\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eOptionally, you can install flash attention 3 for faster speed.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"git clone https://github.com/Dao-AILab/flash-attention # 4f0640d5\ncd flash-attention/hopper\npython setup.py install\"\u003e\u003cpre\u003egit clone https://github.com/Dao-AILab/flash-attention \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e 4f0640d5\u003c/span\u003e\n\u003cspan class=\"pl-c1\"\u003ecd\u003c/span\u003e flash-attention/hopper\npython setup.py install\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eModel Download\u003c/h3\u003e\u003ca id=\"user-content-model-download\" class=\"anchor\" aria-label=\"Permalink: Model Download\" href=\"#model-download\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eOur 11B model supports 256px and 768px resolution. Both T2V and I2V are supported by one model. 🤗 \u003ca href=\"https://huggingface.co/hpcai-tech/Open-Sora-v2\" rel=\"nofollow\"\u003eHuggingface\u003c/a\u003e 🤖 \u003ca href=\"https://modelscope.cn/models/luchentech/Open-Sora-v2\" rel=\"nofollow\"\u003eModelScope\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eDownload from huggingface:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"pip install \u0026quot;huggingface_hub[cli]\u0026quot;\nhuggingface-cli download hpcai-tech/Open-Sora-v2 --local-dir ./ckpts\"\u003e\u003cpre\u003epip install \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003ehuggingface_hub[cli]\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e\nhuggingface-cli download hpcai-tech/Open-Sora-v2 --local-dir ./ckpts\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eDownload from ModelScope:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"pip install modelscope\nmodelscope download hpcai-tech/Open-Sora-v2 --local_dir ./ckpts\"\u003e\u003cpre\u003epip install modelscope\nmodelscope download hpcai-tech/Open-Sora-v2 --local_dir ./ckpts\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eText-to-Video Generation\u003c/h3\u003e\u003ca id=\"user-content-text-to-video-generation\" class=\"anchor\" aria-label=\"Permalink: Text-to-Video Generation\" href=\"#text-to-video-generation\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eOur model is optimized for image-to-video generation, but it can also be used for text-to-video generation. To generate high quality videos, with the help of flux text-to-image model, we build a text-to-image-to-video pipeline. For 256x256 resolution:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"# Generate one given prompt\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u0026quot;raining, sea\u0026quot;\n\n# Save memory with offloading\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u0026quot;raining, sea\u0026quot; --offload True\n\n# Generation with csv\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --dataset.data-path assets/texts/example.csv\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Generate one given prompt\u003c/span\u003e\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Save memory with offloading\u003c/span\u003e\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e --offload True\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Generation with csv\u003c/span\u003e\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --dataset.data-path assets/texts/example.csv\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eFor 768x768 resolution:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"# One GPU\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_768px.py --save-dir samples --prompt \u0026quot;raining, sea\u0026quot;\n\n# Multi-GPU with colossalai sp\ntorchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_768px.py --save-dir samples --prompt \u0026quot;raining, sea\u0026quot;\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e One GPU\u003c/span\u003e\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_768px.py --save-dir samples --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Multi-GPU with colossalai sp\u003c/span\u003e\ntorchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_768px.py --save-dir samples --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eYou can adjust the generation aspect ratio by \u003ccode\u003e--aspect_ratio\u003c/code\u003e and the generation length by \u003ccode\u003e--num_frames\u003c/code\u003e. Candidate values for aspect_ratio includes \u003ccode\u003e16:9\u003c/code\u003e, \u003ccode\u003e9:16\u003c/code\u003e, \u003ccode\u003e1:1\u003c/code\u003e, \u003ccode\u003e2.39:1\u003c/code\u003e. Candidate values for num_frames should be \u003ccode\u003e4k+1\u003c/code\u003e and less than 129.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eYou can also run direct text-to-video by:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"# One GPU for 256px\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --prompt \u0026quot;raining, sea\u0026quot;\n# Multi-GPU for 768px\ntorchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/768px.py --prompt \u0026quot;raining, sea\u0026quot;\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e One GPU for 256px\u003c/span\u003e\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Multi-GPU for 768px\u003c/span\u003e\ntorchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/768px.py --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eImage-to-Video Generation\u003c/h3\u003e\u003ca id=\"user-content-image-to-video-generation\" class=\"anchor\" aria-label=\"Permalink: Image-to-Video Generation\" href=\"#image-to-video-generation\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eGiven a prompt and a reference image, you can generate a video with the following command:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"# 256px\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --cond_type i2v_head --prompt \u0026quot;A plump pig wallows in a muddy pond on a rustic farm, its pink snout poking out as it snorts contentedly. The camera captures the pig's playful splashes, sending ripples through the water under the midday sun. Wooden fences and a red barn stand in the background, framed by rolling green hills. The pig's muddy coat glistens in the sunlight, showcasing the simple pleasures of its carefree life.\u0026quot; --ref assets/texts/i2v.png\n\n# 256px with csv\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --cond_type i2v_head --dataset.data-path assets/texts/i2v.csv\n\n# Multi-GPU 768px\ntorchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/768px.py --cond_type i2v_head --dataset.data-path assets/texts/i2v.csv\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e 256px\u003c/span\u003e\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --cond_type i2v_head --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eA plump pig wallows in a muddy pond on a rustic farm, its pink snout poking out as it snorts contentedly. The camera captures the pig's playful splashes, sending ripples through the water under the midday sun. Wooden fences and a red barn stand in the background, framed by rolling green hills. The pig's muddy coat glistens in the sunlight, showcasing the simple pleasures of its carefree life.\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e --ref assets/texts/i2v.png\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e 256px with csv\u003c/span\u003e\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --cond_type i2v_head --dataset.data-path assets/texts/i2v.csv\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Multi-GPU 768px\u003c/span\u003e\ntorchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/768px.py --cond_type i2v_head --dataset.data-path assets/texts/i2v.csv\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eAdvanced Usage\u003c/h2\u003e\u003ca id=\"user-content-advanced-usage\" class=\"anchor\" aria-label=\"Permalink: Advanced Usage\" href=\"#advanced-usage\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eMotion Score\u003c/h3\u003e\u003ca id=\"user-content-motion-score\" class=\"anchor\" aria-label=\"Permalink: Motion Score\" href=\"#motion-score\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eDuring training, we provide motion score into the text prompt. During inference, you can use the following command to generate videos with motion score (the default score is 4):\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u0026quot;raining, sea\u0026quot; --motion-score 4\"\u003e\u003cpre\u003etorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e --motion-score 4\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eWe also provide a dynamic motion score evaluator. After setting your OpenAI API key, you can use the following command to evaluate the motion score of a video:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u0026quot;raining, sea\u0026quot; --motion-score dynamic\"\u003e\u003cpre\u003etorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e --motion-score dynamic\u003c/pre\u003e\u003c/div\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eScore\u003c/th\u003e\n\u003cth\u003e1\u003c/th\u003e\n\u003cth\u003e4\u003c/th\u003e\n\u003cth\u003e7\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://github.com/hpcaitech/Open-Sora-Demo/blob/main/demo/v2.0/motion_score_1.gif\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/motion_score_1.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://github.com/hpcaitech/Open-Sora-Demo/blob/main/demo/v2.0/motion_score_4.gif\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/motion_score_4.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://github.com/hpcaitech/Open-Sora-Demo/blob/main/demo/v2.0/motion_score_7.gif\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/motion_score_7.gif\" width=\"\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003ePrompt Refine\u003c/h3\u003e\u003ca id=\"user-content-prompt-refine\" class=\"anchor\" aria-label=\"Permalink: Prompt Refine\" href=\"#prompt-refine\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eWe take advantage of ChatGPT to refine the prompt. You can use the following command to refine the prompt. The function is available for both text-to-video and image-to-video generation.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"export OPENAI_API_KEY=sk-xxxx\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u0026quot;raining, sea\u0026quot; --refine-prompt True\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003eexport\u003c/span\u003e OPENAI_API_KEY=sk-xxxx\ntorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e --refine-prompt True\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eReproductivity\u003c/h3\u003e\u003ca id=\"user-content-reproductivity\" class=\"anchor\" aria-label=\"Permalink: Reproductivity\" href=\"#reproductivity\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eTo make the results reproducible, you can set the random seed by:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u0026quot;raining, sea\u0026quot; --sampling_option.seed 42 --seed 42\"\u003e\u003cpre\u003etorchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003eraining, sea\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e --sampling_option.seed 42 --seed 42\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eUse \u003ccode\u003e--num-sample k\u003c/code\u003e to generate \u003ccode\u003ek\u003c/code\u003e samples for each prompt.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eComputational Efficiency\u003c/h2\u003e\u003ca id=\"user-content-computational-efficiency\" class=\"anchor\" aria-label=\"Permalink: Computational Efficiency\" href=\"#computational-efficiency\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eWe test the computational efficiency of text-to-video on H100/H800 GPU. For 256x256, we use colossalai's tensor parallelism, and \u003ccode\u003e--offload True\u003c/code\u003e is used. For 768x768, we use colossalai's sequence parallelism. All use number of steps 50. The results are presented in the format: \u003cmath-renderer class=\"js-inline-math\" style=\"display: inline-block\" data-static-url=\"https://github.githubassets.com/static\" data-run-id=\"a63166519019d3dd05a4348534651b27\"\u003e$\\color{blue}{\\text{Total time (s)}}/\\color{red}{\\text{peak GPU memory (GB)}}$\u003c/math-renderer\u003e\u003c/p\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eResolution\u003c/th\u003e\n\u003cth\u003e1x GPU\u003c/th\u003e\n\u003cth\u003e2x GPUs\u003c/th\u003e\n\u003cth\u003e4x GPUs\u003c/th\u003e\n\u003cth\u003e8x GPUs\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e256x256\u003c/td\u003e\n\u003ctd\u003e\u003cmath-renderer class=\"js-inline-math\" style=\"display: inline-block\" data-static-url=\"https://github.githubassets.com/static\" data-run-id=\"a63166519019d3dd05a4348534651b27\"\u003e$\\color{blue}{60}/\\color{red}{52.5}$\u003c/math-renderer\u003e\u003c/td\u003e\n\u003ctd\u003e\u003cmath-renderer class=\"js-inline-math\" style=\"display: inline-block\" data-static-url=\"https://github.githubassets.com/static\" data-run-id=\"a63166519019d3dd05a4348534651b27\"\u003e$\\color{blue}{40}/\\color{red}{44.3}$\u003c/math-renderer\u003e\u003c/td\u003e\n\u003ctd\u003e\u003cmath-renderer class=\"js-inline-math\" style=\"display: inline-block\" data-static-url=\"https://github.githubassets.com/static\" data-run-id=\"a63166519019d3dd05a4348534651b27\"\u003e$\\color{blue}{34}/\\color{red}{44.3}$\u003c/math-renderer\u003e\u003c/td\u003e\n\u003ctd\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e768x768\u003c/td\u003e\n\u003ctd\u003e\u003cmath-renderer class=\"js-inline-math\" style=\"display: inline-block\" data-static-url=\"https://github.githubassets.com/static\" data-run-id=\"a63166519019d3dd05a4348534651b27\"\u003e$\\color{blue}{1656}/\\color{red}{60.3}$\u003c/math-renderer\u003e\u003c/td\u003e\n\u003ctd\u003e\u003cmath-renderer class=\"js-inline-math\" style=\"display: inline-block\" data-static-url=\"https://github.githubassets.com/static\" data-run-id=\"a63166519019d3dd05a4348534651b27\"\u003e$\\color{blue}{863}/\\color{red}{48.3}$\u003c/math-renderer\u003e\u003c/td\u003e\n\u003ctd\u003e\u003cmath-renderer class=\"js-inline-math\" style=\"display: inline-block\" data-static-url=\"https://github.githubassets.com/static\" data-run-id=\"a63166519019d3dd05a4348534651b27\"\u003e$\\color{blue}{466}/\\color{red}{44.3}$\u003c/math-renderer\u003e\u003c/td\u003e\n\u003ctd\u003e\u003cmath-renderer class=\"js-inline-math\" style=\"display: inline-block\" data-static-url=\"https://github.githubassets.com/static\" data-run-id=\"a63166519019d3dd05a4348534651b27\"\u003e$\\color{blue}{276}/\\color{red}{44.3}$\u003c/math-renderer\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eEvaluation\u003c/h2\u003e\u003ca id=\"user-content-evaluation\" class=\"anchor\" aria-label=\"Permalink: Evaluation\" href=\"#evaluation\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eOn \u003ca href=\"https://huggingface.co/spaces/Vchitect/VBench_Leaderboard\" rel=\"nofollow\"\u003eVBench\u003c/a\u003e, Open-Sora 2.0 significantly narrows the gap with OpenAI’s Sora, reducing it from 4.52% → 0.69% compared to Open-Sora 1.2.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://github.com/hpcaitech/Open-Sora-Demo/blob/main/readme/v2_vbench.png\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/readme/v2_vbench.png\" alt=\"VBench\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eHuman preference results show our model is on par with HunyuanVideo 11B and Step-Video 30B.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://github.com/hpcaitech/Open-Sora-Demo/blob/main/readme/v2_winrate.png\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/readme/v2_winrate.png\" alt=\"Win Rate\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eWith strong performance, Open-Sora 2.0 is cost-effective.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://github.com/hpcaitech/Open-Sora-Demo/blob/main/readme/v2_cost.png\"\u003e\u003cimg src=\"https://github.com/hpcaitech/Open-Sora-Demo/raw/main/readme/v2_cost.png\" alt=\"Cost\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eContribution\u003c/h2\u003e\u003ca id=\"user-content-contribution\" class=\"anchor\" aria-label=\"Permalink: Contribution\" href=\"#contribution\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThanks goes to these wonderful contributors:\u003c/p\u003e\n\u003ca href=\"https://github.com/hpcaitech/Open-Sora/graphs/contributors\"\u003e\n \u003cimg src=\"https://camo.githubusercontent.com/5cdddbfc17e31a502cd3dded290742ffb4d51dfa670ba13e6467959245f94ba4/68747470733a2f2f636f6e747269622e726f636b732f696d6167653f7265706f3d6870636169746563682f4f70656e2d536f7261\" data-canonical-src=\"https://contrib.rocks/image?repo=hpcaitech/Open-Sora\" style=\"max-width: 100%;\"\u003e\n\u003c/a\u003e\n\u003cp dir=\"auto\"\u003eIf you wish to contribute to this project, please refer to the \u003ca href=\"/hpcaitech/Open-Sora/blob/main/CONTRIBUTING.md\"\u003eContribution Guideline\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eAcknowledgement\u003c/h2\u003e\u003ca id=\"user-content-acknowledgement\" class=\"anchor\" aria-label=\"Permalink: Acknowledgement\" href=\"#acknowledgement\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eHere we only list a few of the projects. For other works and datasets, please refer to our report.\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/hpcaitech/ColossalAI\"\u003eColossalAI\u003c/a\u003e: A powerful large model parallel acceleration and optimization\nsystem.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/facebookresearch/DiT\"\u003eDiT\u003c/a\u003e: Scalable Diffusion Models with Transformers.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/NUS-HPC-AI-Lab/OpenDiT\"\u003eOpenDiT\u003c/a\u003e: An acceleration for DiT training. We adopt valuable acceleration\nstrategies for training progress from OpenDiT.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/PixArt-alpha/PixArt-alpha\"\u003ePixArt\u003c/a\u003e: An open-source DiT-based text-to-image model.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/black-forest-labs/flux\"\u003eFlux\u003c/a\u003e: A powerful text-to-image generation model.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/Vchitect/Latte\"\u003eLatte\u003c/a\u003e: An attempt to efficiently train DiT for video.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/Tencent/HunyuanVideo/tree/main?tab=readme-ov-file\"\u003eHunyuanVideo\u003c/a\u003e: Open-Source text-to-video model.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://huggingface.co/stabilityai/sd-vae-ft-mse-original\" rel=\"nofollow\"\u003eStabilityAI VAE\u003c/a\u003e: A powerful image VAE model.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/mit-han-lab/efficientvit\"\u003eDC-AE\u003c/a\u003e: Deep Compression AutoEncoder for image compression.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/openai/CLIP\"\u003eCLIP\u003c/a\u003e: A powerful text-image embedding model.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/google-research/text-to-text-transfer-transformer\"\u003eT5\u003c/a\u003e: A powerful text encoder.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/haotian-liu/LLaVA\"\u003eLLaVA\u003c/a\u003e: A powerful image captioning model based on \u003ca href=\"https://huggingface.co/mistralai/Mistral-7B-v0.1\" rel=\"nofollow\"\u003eMistral-7B\u003c/a\u003e and \u003ca href=\"https://huggingface.co/01-ai/Yi-34B\" rel=\"nofollow\"\u003eYi-34B\u003c/a\u003e.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/magic-research/PLLaVA\"\u003ePLLaVA\u003c/a\u003e: A powerful video captioning model.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/mira-space/MiraData\"\u003eMiraData\u003c/a\u003e: A large-scale video dataset with long durations and structured caption.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eCitation\u003c/h2\u003e\u003ca id=\"user-content-citation\" class=\"anchor\" aria-label=\"Permalink: Citation\" href=\"#citation\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"highlight highlight-text-bibtex notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"@article{opensora,\n title={Open-sora: Democratizing efficient video production for all},\n author={Zheng, Zangwei and Peng, Xiangyu and Yang, Tianji and Shen, Chenhui and Li, Shenggui and Liu, Hongxin and Zhou, Yukun and Li, Tianyi and You, Yang},\n journal={arXiv preprint arXiv:2412.20404},\n year={2024}\n}\n\n@article{opensora2,\n title={Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k}, \n author={Xiangyu Peng and Zangwei Zheng and Chenhui Shen and Tom Young and Xinying Guo and Binluo Wang and Hang Xu and Hongxin Liu and Mingyan Jiang and Wenjun Li and Yuhui Wang and Anbang Ye and Gang Ren and Qianran Ma and Wanying Liang and Xiang Lian and Xiwen Wu and Yuting Zhong and Zhuangyan Li and Chaoyu Gong and Guojun Lei and Leijun Cheng and Limin Zhang and Minghao Li and Ruijie Zhang and Silan Hu and Shijie Huang and Xiaokang Wang and Yuanheng Zhao and Yuqi Wang and Ziang Wei and Yang You},\n year={2025},\n journal={arXiv preprint arXiv:2503.09642},\n}\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003e@article\u003c/span\u003e{\u003cspan class=\"pl-en\"\u003eopensora\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003etitle\u003c/span\u003e=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e{\u003c/span\u003eOpen-sora: Democratizing efficient video production for all\u003cspan class=\"pl-pds\"\u003e}\u003c/span\u003e\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003eauthor\u003c/span\u003e=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e{\u003c/span\u003eZheng, Zangwei and Peng, Xiangyu and Yang, Tianji and Shen, Chenhui and Li, Shenggui and Liu, Hongxin and Zhou, Yukun and Li, Tianyi and You, Yang\u003cspan class=\"pl-pds\"\u003e}\u003c/span\u003e\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003ejournal\u003c/span\u003e=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e{\u003c/span\u003earXiv preprint arXiv:2412.20404\u003cspan class=\"pl-pds\"\u003e}\u003c/span\u003e\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003eyear\u003c/span\u003e=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e{\u003c/span\u003e2024\u003cspan class=\"pl-pds\"\u003e}\u003c/span\u003e\u003c/span\u003e\n}\n\n\u003cspan class=\"pl-k\"\u003e@article\u003c/span\u003e{\u003cspan class=\"pl-en\"\u003eopensora2\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003etitle\u003c/span\u003e=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e{\u003c/span\u003eOpen-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k\u003cspan class=\"pl-pds\"\u003e}\u003c/span\u003e\u003c/span\u003e, \n \u003cspan class=\"pl-s\"\u003eauthor\u003c/span\u003e=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e{\u003c/span\u003eXiangyu Peng and Zangwei Zheng and Chenhui Shen and Tom Young and Xinying Guo and Binluo Wang and Hang Xu and Hongxin Liu and Mingyan Jiang and Wenjun Li and Yuhui Wang and Anbang Ye and Gang Ren and Qianran Ma and Wanying Liang and Xiang Lian and Xiwen Wu and Yuting Zhong and Zhuangyan Li and Chaoyu Gong and Guojun Lei and Leijun Cheng and Limin Zhang and Minghao Li and Ruijie Zhang and Silan Hu and Shijie Huang and Xiaokang Wang and Yuanheng Zhao and Yuqi Wang and Ziang Wei and Yang You\u003cspan class=\"pl-pds\"\u003e}\u003c/span\u003e\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003eyear\u003c/span\u003e=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e{\u003c/span\u003e2025\u003cspan class=\"pl-pds\"\u003e}\u003c/span\u003e\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003ejournal\u003c/span\u003e=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e{\u003c/span\u003earXiv preprint arXiv:2503.09642\u003cspan class=\"pl-pds\"\u003e}\u003c/span\u003e\u003c/span\u003e,\n}\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eStar History\u003c/h2\u003e\u003ca id=\"user-content-star-history\" class=\"anchor\" aria-label=\"Permalink: Star History\" href=\"#star-history\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003ca href=\"https://star-history.com/#hpcaitech/Open-Sora\u0026amp;Date\" rel=\"nofollow\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/3fe4ff7323fb8ded741d90823b8c8937c6f43e029539c3ca8721a70f0bd1fc2e/68747470733a2f2f6170692e737461722d686973746f72792e636f6d2f7376673f7265706f733d6870636169746563682f4f70656e2d536f726126747970653d44617465\" alt=\"Star History Chart\" data-canonical-src=\"https://api.star-history.com/svg?repos=hpcaitech/Open-Sora\u0026amp;type=Date\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003c/article\u003e","loaded":true,"timedOut":false,"errorMessage":null,"headerInfo":{"toc":[{"level":2,"text":"Open-Sora: Democratizing Efficient Video Production for All","anchor":"open-sora-democratizing-efficient-video-production-for-all","htmlText":"Open-Sora: Democratizing Efficient Video Production for All"},{"level":2,"text":"📰 News","anchor":"-news","htmlText":"📰 News"},{"level":2,"text":"🎥 Latest Demo","anchor":"-latest-demo","htmlText":"🎥 Latest Demo"},{"level":2,"text":"🔆 Reports","anchor":"-reports","htmlText":"🔆 Reports"},{"level":2,"text":"Quickstart","anchor":"quickstart","htmlText":"Quickstart"},{"level":3,"text":"Installation","anchor":"installation","htmlText":"Installation"},{"level":3,"text":"Model Download","anchor":"model-download","htmlText":"Model Download"},{"level":3,"text":"Text-to-Video Generation","anchor":"text-to-video-generation","htmlText":"Text-to-Video Generation"},{"level":3,"text":"Image-to-Video Generation","anchor":"image-to-video-generation","htmlText":"Image-to-Video Generation"},{"level":2,"text":"Advanced Usage","anchor":"advanced-usage","htmlText":"Advanced Usage"},{"level":3,"text":"Motion Score","anchor":"motion-score","htmlText":"Motion Score"},{"level":3,"text":"Prompt Refine","anchor":"prompt-refine","htmlText":"Prompt Refine"},{"level":3,"text":"Reproductivity","anchor":"reproductivity","htmlText":"Reproductivity"},{"level":2,"text":"Computational Efficiency","anchor":"computational-efficiency","htmlText":"Computational Efficiency"},{"level":2,"text":"Evaluation","anchor":"evaluation","htmlText":"Evaluation"},{"level":2,"text":"Contribution","anchor":"contribution","htmlText":"Contribution"},{"level":2,"text":"Acknowledgement","anchor":"acknowledgement","htmlText":"Acknowledgement"},{"level":2,"text":"Citation","anchor":"citation","htmlText":"Citation"},{"level":2,"text":"Star History","anchor":"star-history","htmlText":"Star History"}],"siteNavLoginPath":"/login?return_to=https%3A%2F%2Fgithub.com%2Fhpcaitech%2FOpen-Sora"}},{"displayName":"LICENSE","repoName":"Open-Sora","refName":"main","path":"LICENSE","preferredFileType":"license","tabName":"Apache-2.0","richText":null,"loaded":false,"timedOut":false,"errorMessage":null,"headerInfo":{"toc":null,"siteNavLoginPath":"/login?return_to=https%3A%2F%2Fgithub.com%2Fhpcaitech%2FOpen-Sora"}}],"overviewFilesProcessingTime":0}},"appPayload":{"helpUrl":"https://docs.github.com","findFileWorkerPath":"/assets-cdn/worker/find-file-worker-7d7eb7c71814.js","findInFileWorkerPath":"/assets-cdn/worker/find-in-file-worker-96e76d5fdb2c.js","githubDevUrl":null,"enabled_features":{"copilot_workspace":null,"code_nav_ui_events":false,"overview_shared_code_dropdown_button":false,"react_blob_overlay":false,"accessible_code_button":true,"github_models_repo_integration":false}}}}</script> <div data-target="react-partial.reactRoot"><style data-styled="true" 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src="https://camo.githubusercontent.com/ce33304a9340ae787c7cda8d19b6f3a343872353b0477771508e64a145c95fa3/68747470733a2f2f696d672e736869656c64732e696f2f62616467652fe5beaee4bfa12de5b08fe58aa9e6898be58aa0e7bea42d677265656e3f6c6f676f3d77656368617426" data-canonical-src="https://img.shields.io/badge/微信-小助手加群-green?logo=wechat&" style="max-width: 100%;"></a> </div> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Open-Sora: Democratizing Efficient Video Production for All</h2><a id="user-content-open-sora-democratizing-efficient-video-production-for-all" class="anchor" aria-label="Permalink: Open-Sora: Democratizing Efficient Video Production for All" href="#open-sora-democratizing-efficient-video-production-for-all"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">We design and implement <strong>Open-Sora</strong>, an initiative dedicated to <strong>efficiently</strong> producing high-quality video. We hope to make the model, tools and all details accessible to all. By embracing <strong>open-source</strong> principles, Open-Sora not only democratizes access to advanced video generation techniques, but also offers a streamlined and user-friendly platform that simplifies the complexities of video generation. With Open-Sora, our goal is to foster innovation, creativity, and inclusivity within the field of content creation.</p> <p dir="auto">🎬 For a professional AI video-generation product, try <a href="https://video-ocean.com/" rel="nofollow">Video Ocean</a> — powered by a superior model.</p> <div align="center" dir="auto"> <a href="https://video-ocean.com/" rel="nofollow"> <img src="https://github.com/hpcaitech/public_assets/raw/main/colossalai/img/3.gif" width="850" data-animated-image="" style="max-width: 100%;"> </a> </div> <div align="center" dir="auto"> <a href="https://hpc-ai.com/?utm_source=github&utm_medium=social&utm_campaign=promotion-opensora" rel="nofollow"> <img src="https://github.com/hpcaitech/public_assets/raw/main/colossalai/img/1.gif" width="850" data-animated-image="" style="max-width: 100%;"> </a> </div> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">📰 News</h2><a id="user-content--news" class="anchor" aria-label="Permalink: 📰 News" href="#-news"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <ul dir="auto"> <li><strong>[2025.03.12]</strong> 🔥 We released <strong>Open-Sora 2.0</strong> (11B). 🎬 11B model achieves <a href="#evaluation">on-par performance</a> with 11B HunyuanVideo & 30B Step-Video on 📐VBench & 📊Human Preference. 🛠️ Fully open-source: checkpoints and training codes for training with only <strong>$200K</strong>. <a href="https://arxiv.org/abs/2503.09642v1" rel="nofollow">[report]</a></li> <li><strong>[2025.02.20]</strong> 🔥 We released <strong>Open-Sora 1.3</strong> (1B). With the upgraded VAE and Transformer architecture, the quality of our generated videos has been greatly improved 🚀. <a href="#open-sora-13-model-weights">[checkpoints]</a> <a href="/hpcaitech/Open-Sora/blob/main/docs/report_04.md">[report]</a> <a href="https://huggingface.co/spaces/hpcai-tech/open-sora" rel="nofollow">[demo]</a></li> <li><strong>[2024.12.23]</strong> The development cost of video generation models has saved by 50%! Open-source solutions are now available with H200 GPU vouchers. <a href="https://company.hpc-ai.com/blog/the-development-cost-of-video-generation-models-has-saved-by-50-open-source-solutions-are-now-available-with-h200-gpu-vouchers" rel="nofollow">[blog]</a> <a href="https://github.com/hpcaitech/Open-Sora/blob/main/scripts/train.py">[code]</a> <a href="https://colossalai.org/zh-Hans/docs/get_started/bonus/" rel="nofollow">[vouchers]</a></li> <li><strong>[2024.06.17]</strong> We released <strong>Open-Sora 1.2</strong>, which includes <strong>3D-VAE</strong>, <strong>rectified flow</strong>, and <strong>score condition</strong>. The video quality is greatly improved. <a href="#open-sora-12-model-weights">[checkpoints]</a> <a href="/hpcaitech/Open-Sora/blob/main/docs/report_03.md">[report]</a> <a href="https://arxiv.org/abs/2412.20404" rel="nofollow">[arxiv]</a></li> <li><strong>[2024.04.25]</strong> 🤗 We released the <a href="https://huggingface.co/spaces/hpcai-tech/open-sora" rel="nofollow">Gradio demo for Open-Sora</a> on Hugging Face Spaces.</li> <li><strong>[2024.04.25]</strong> We released <strong>Open-Sora 1.1</strong>, which supports <strong>2s~15s, 144p to 720p, any aspect ratio</strong> text-to-image, <strong>text-to-video, image-to-video, video-to-video, infinite time</strong> generation. In addition, a full video processing pipeline is released. <a href="#open-sora-11-model-weights">[checkpoints]</a> <a href="/hpcaitech/Open-Sora/blob/main/docs/report_02.md">[report]</a></li> <li><strong>[2024.03.18]</strong> We released <strong>Open-Sora 1.0</strong>, a fully open-source project for video generation. Open-Sora 1.0 supports a full pipeline of video data preprocessing, training with <a href="https://github.com/hpcaitech/ColossalAI"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/readme/colossal_ai.png" width="8%" style="max-width: 100%;"></a> acceleration, inference, and more. Our model can produce 2s 512x512 videos with only 3 days training. <a href="#open-sora-10-model-weights">[checkpoints]</a> <a href="https://hpc-ai.com/blog/open-sora-v1.0" rel="nofollow">[blog]</a> <a href="/hpcaitech/Open-Sora/blob/main/docs/report_01.md">[report]</a></li> <li><strong>[2024.03.04]</strong> Open-Sora provides training with 46% cost reduction. <a href="https://hpc-ai.com/blog/open-sora" rel="nofollow">[blog]</a></li> </ul> <p dir="auto">📍 Since Open-Sora is under active development, we remain different branches for different versions. The latest version is <a href="https://github.com/hpcaitech/Open-Sora">main</a>. Old versions include: <a href="https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.0">v1.0</a>, <a href="https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.1">v1.1</a>, <a href="https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.2">v1.2</a>, <a href="https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.3">v1.3</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">🎥 Latest Demo</h2><a id="user-content--latest-demo" class="anchor" aria-label="Permalink: 🎥 Latest Demo" href="#-latest-demo"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Demos are presented in compressed GIF format for convenience. For original quality samples and their corresponding prompts, please visit our <a href="https://hpcaitech.github.io/Open-Sora/" rel="nofollow">Gallery</a>.</p> <markdown-accessiblity-table><table> <thead> <tr> <th><strong>5s 1024×576</strong></th> <th><strong>5s 576×1024</strong></th> <th><strong>5s 576×1024</strong></th> </tr> </thead> <tbody> <tr> <td><a href="https://streamable.com/e/8g9y9h?autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/ft_0001_1_1.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/k50mnv?autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/movie_0160.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/bzrn9n?autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/movie_0017.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td><a href="https://streamable.com/e/dsv8da?autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/ft_0012_1_1.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/3wif07?autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/douyin_0005.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/us2w7h?autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/movie_0037.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td><a href="https://streamable.com/e/yfwk8i?autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/ft_0055_1_1.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/jgjil0?autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/sora_0019.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/lsoai1?autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/movie_0463.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> </tbody> </table></markdown-accessiblity-table> <details> <summary>OpenSora 1.3 Demo</summary> <markdown-accessiblity-table><table> <thead> <tr> <th><strong>5s 720×1280</strong></th> <th><strong>5s 720×1280</strong></th> <th><strong>5s 720×1280</strong></th> </tr> </thead> <tbody> <tr> <td><a href="https://streamable.com/e/r0imrp?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_tomato.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/hfvjkh?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_fisherman.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/kutmma?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_girl2.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td><a href="https://streamable.com/e/osn1la?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_grape.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/l1pzws?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_mushroom.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/2vqari?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_parrot.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td><a href="https://streamable.com/e/1in7d6?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_trans.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/e9bi4o?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_bear.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/09z7xi?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_futureflower.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td><a href="https://streamable.com/e/16c3hk?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_fire.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/wi250w?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_man.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://streamable.com/e/vw5b64?quality=highest&autoplay=1" rel="nofollow"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.3/demo_black.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> </tbody> </table></markdown-accessiblity-table> </details> <details> <summary>OpenSora 1.2 Demo</summary> <markdown-accessiblity-table><table> <thead> <tr> <th><strong>4s 720×1280</strong></th> <th><strong>4s 720×1280</strong></th> <th><strong>4s 720×1280</strong></th> </tr> </thead> <tbody> <tr> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/7895aab6-ed23-488c-8486-091480c26327"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0013.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/20f07c7b-182b-4562-bbee-f1df74c86c9a"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_1718.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/3d897e0d-dc21-453a-b911-b3bda838acc2"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0087.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/644bf938-96ce-44aa-b797-b3c0b513d64c"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0052.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/272d88ac-4b4a-484d-a665-8d07431671d0"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_1719.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/ebbac621-c34e-4bb4-9543-1c34f8989764"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0002.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/a1e3a1a3-4abd-45f5-8df2-6cced69da4ca"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0011.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/d6ce9c13-28e1-4dff-9644-cc01f5f11926"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0004.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/561978f8-f1b0-4f4d-ae7b-45bec9001b4a"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.2/sample_0061.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> </tbody> </table></markdown-accessiblity-table> </details> <details> <summary>OpenSora 1.1 Demo</summary> <markdown-accessiblity-table><table> <thead> <tr> <th><strong>2s 240×426</strong></th> <th><strong>2s 240×426</strong></th> </tr> </thead> <tbody> <tr> <td><a href="https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c31ebc52-de39-4a4e-9b1e-9211d45e05b2"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sample_16x240x426_9.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c31ebc52-de39-4a4e-9b1e-9211d45e05b2"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x240x426_26.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td><a href="https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/f7ce4aaa-528f-40a8-be7a-72e61eaacbbd"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x240x426_27.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/5d58d71e-1fda-4d90-9ad3-5f2f7b75c6a9"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x240x426_40.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> </tbody> </table></markdown-accessiblity-table> <markdown-accessiblity-table><table> <thead> <tr> <th><strong>2s 426×240</strong></th> <th><strong>4s 480×854</strong></th> </tr> </thead> <tbody> <tr> <td><a href="https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/34ecb4a0-4eef-4286-ad4c-8e3a87e5a9fd"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x426x240_24.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c1619333-25d7-42ba-a91c-18dbc1870b18"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sample_32x480x854_9.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> </tbody> </table></markdown-accessiblity-table> <markdown-accessiblity-table><table> <thead> <tr> <th><strong>16s 320×320</strong></th> <th><strong>16s 224×448</strong></th> <th><strong>2s 426×240</strong></th> </tr> </thead> <tbody> <tr> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/3cab536e-9b43-4b33-8da8-a0f9cf842ff2"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sample_16s_320x320.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/9fb0b9e0-c6f4-4935-b29e-4cac10b373c4"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sample_16s_224x448.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/3e892ad2-9543-4049-b005-643a4c1bf3bf"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.1/sora_16x426x240_3.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> </tbody> </table></markdown-accessiblity-table> </details> <details> <summary>OpenSora 1.0 Demo</summary> <markdown-accessiblity-table><table> <thead> <tr> <th><strong>2s 512×512</strong></th> <th><strong>2s 512×512</strong></th> <th><strong>2s 512×512</strong></th> </tr> </thead> <tbody> <tr> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/de1963d3-b43b-4e68-a670-bb821ebb6f80"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_0.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/13f8338f-3d42-4b71-8142-d234fbd746cc"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_1.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/fa6a65a6-e32a-4d64-9a9e-eabb0ebb8c16"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_2.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td>A serene night scene in a forested area. [...] The video is a time-lapse, capturing the transition from day to night, with the lake and forest serving as a constant backdrop.</td> <td>A soaring drone footage captures the majestic beauty of a coastal cliff, [...] The water gently laps at the rock base and the greenery that clings to the top of the cliff.</td> <td>The majestic beauty of a waterfall cascading down a cliff into a serene lake. [...] The camera angle provides a bird's eye view of the waterfall.</td> </tr> <tr> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/64232f84-1b36-4750-a6c0-3e610fa9aa94"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_3.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/983a1965-a374-41a7-a76b-c07941a6c1e9"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_4.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://github.com/hpcaitech/Open-Sora/assets/99191637/ec10c879-9767-4c31-865f-2e8d6cf11e65"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v1.0/sample_5.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td>A bustling city street at night, filled with the glow of car headlights and the ambient light of streetlights. [...]</td> <td>The vibrant beauty of a sunflower field. The sunflowers are arranged in neat rows, creating a sense of order and symmetry. [...]</td> <td>A serene underwater scene featuring a sea turtle swimming through a coral reef. The turtle, with its greenish-brown shell [...]</td> </tr> </tbody> </table></markdown-accessiblity-table> <p dir="auto">Videos are downsampled to <code>.gif</code> for display. Click for original videos. Prompts are trimmed for display, see <a href="/hpcaitech/Open-Sora/blob/main/assets/texts/t2v_samples.txt">here</a> for full prompts.</p> </details> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">🔆 Reports</h2><a id="user-content--reports" class="anchor" aria-label="Permalink: 🔆 Reports" href="#-reports"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <ul dir="auto"> <li><strong><a href="https://arxiv.org/abs/2503.09642v1" rel="nofollow">Tech Report of Open-Sora 2.0</a></strong></li> <li><strong><a href="/hpcaitech/Open-Sora/blob/main/docs/train.md">Step by step to train or finetune your own model</a></strong></li> <li><strong><a href="/hpcaitech/Open-Sora/blob/main/docs/ae.md">Step by step to train and evaluate an video autoencoder</a></strong></li> <li><strong><a href="/hpcaitech/Open-Sora/blob/main/docs/hcae.md">Visit the high compression video autoencoder</a></strong></li> <li>Reports of previous version (better see in according branch): <ul dir="auto"> <li><a href="/hpcaitech/Open-Sora/blob/main/docs/report_04.md">Open-Sora 1.3</a>: shift-window attention, unified spatial-temporal VAE, etc.</li> <li><a href="/hpcaitech/Open-Sora/blob/main/docs/report_03.md">Open-Sora 1.2</a>, <a href="https://arxiv.org/abs/2412.20404" rel="nofollow">Tech Report</a>: rectified flow, 3d-VAE, score condition, evaluation, etc.</li> <li><a href="/hpcaitech/Open-Sora/blob/main/docs/report_02.md">Open-Sora 1.1</a>: multi-resolution/length/aspect-ratio, image/video conditioning/editing, data preprocessing, etc.</li> <li><a href="/hpcaitech/Open-Sora/blob/main/docs/report_01.md">Open-Sora 1.0</a>: architecture, captioning, etc.</li> </ul> </li> </ul> <p dir="auto">📍 Since Open-Sora is under active development, we remain different branches for different versions. The latest version is <a href="https://github.com/hpcaitech/Open-Sora">main</a>. Old versions include: <a href="https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.0">v1.0</a>, <a href="https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.1">v1.1</a>, <a href="https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.2">v1.2</a>, <a href="https://github.com/hpcaitech/Open-Sora/tree/opensora/v1.3">v1.3</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Quickstart</h2><a id="user-content-quickstart" class="anchor" aria-label="Permalink: Quickstart" href="#quickstart"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Installation</h3><a id="user-content-installation" class="anchor" aria-label="Permalink: Installation" href="#installation"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="# create a virtual env and activate (conda as an example) conda create -n opensora python=3.10 conda activate opensora # download the repo git clone https://github.com/hpcaitech/Open-Sora cd Open-Sora # Ensure torch >= 2.4.0 pip install -v . # for development mode, `pip install -v -e .` pip install xformers==0.0.27.post2 --index-url https://download.pytorch.org/whl/cu121 # install xformers according to your cuda version pip install flash-attn --no-build-isolation"><pre><span class="pl-c"><span class="pl-c">#</span> create a virtual env and activate (conda as an example)</span> conda create -n opensora python=3.10 conda activate opensora <span class="pl-c"><span class="pl-c">#</span> download the repo</span> git clone https://github.com/hpcaitech/Open-Sora <span class="pl-c1">cd</span> Open-Sora <span class="pl-c"><span class="pl-c">#</span> Ensure torch >= 2.4.0</span> pip install -v <span class="pl-c1">.</span> <span class="pl-c"><span class="pl-c">#</span> for development mode, `pip install -v -e .`</span> pip install xformers==0.0.27.post2 --index-url https://download.pytorch.org/whl/cu121 <span class="pl-c"><span class="pl-c">#</span> install xformers according to your cuda version</span> pip install flash-attn --no-build-isolation</pre></div> <p dir="auto">Optionally, you can install flash attention 3 for faster speed.</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="git clone https://github.com/Dao-AILab/flash-attention # 4f0640d5 cd flash-attention/hopper python setup.py install"><pre>git clone https://github.com/Dao-AILab/flash-attention <span class="pl-c"><span class="pl-c">#</span> 4f0640d5</span> <span class="pl-c1">cd</span> flash-attention/hopper python setup.py install</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Model Download</h3><a id="user-content-model-download" class="anchor" aria-label="Permalink: Model Download" href="#model-download"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Our 11B model supports 256px and 768px resolution. Both T2V and I2V are supported by one model. 🤗 <a href="https://huggingface.co/hpcai-tech/Open-Sora-v2" rel="nofollow">Huggingface</a> 🤖 <a href="https://modelscope.cn/models/luchentech/Open-Sora-v2" rel="nofollow">ModelScope</a>.</p> <p dir="auto">Download from huggingface:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="pip install "huggingface_hub[cli]" huggingface-cli download hpcai-tech/Open-Sora-v2 --local-dir ./ckpts"><pre>pip install <span class="pl-s"><span class="pl-pds">"</span>huggingface_hub[cli]<span class="pl-pds">"</span></span> huggingface-cli download hpcai-tech/Open-Sora-v2 --local-dir ./ckpts</pre></div> <p dir="auto">Download from ModelScope:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="pip install modelscope modelscope download hpcai-tech/Open-Sora-v2 --local_dir ./ckpts"><pre>pip install modelscope modelscope download hpcai-tech/Open-Sora-v2 --local_dir ./ckpts</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Text-to-Video Generation</h3><a id="user-content-text-to-video-generation" class="anchor" aria-label="Permalink: Text-to-Video Generation" href="#text-to-video-generation"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Our model is optimized for image-to-video generation, but it can also be used for text-to-video generation. To generate high quality videos, with the help of flux text-to-image model, we build a text-to-image-to-video pipeline. For 256x256 resolution:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="# Generate one given prompt torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt "raining, sea" # Save memory with offloading torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt "raining, sea" --offload True # Generation with csv torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --dataset.data-path assets/texts/example.csv"><pre><span class="pl-c"><span class="pl-c">#</span> Generate one given prompt</span> torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span> <span class="pl-c"><span class="pl-c">#</span> Save memory with offloading</span> torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span> --offload True <span class="pl-c"><span class="pl-c">#</span> Generation with csv</span> torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --dataset.data-path assets/texts/example.csv</pre></div> <p dir="auto">For 768x768 resolution:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="# One GPU torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_768px.py --save-dir samples --prompt "raining, sea" # Multi-GPU with colossalai sp torchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_768px.py --save-dir samples --prompt "raining, sea""><pre><span class="pl-c"><span class="pl-c">#</span> One GPU</span> torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_768px.py --save-dir samples --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span> <span class="pl-c"><span class="pl-c">#</span> Multi-GPU with colossalai sp</span> torchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_768px.py --save-dir samples --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span></pre></div> <p dir="auto">You can adjust the generation aspect ratio by <code>--aspect_ratio</code> and the generation length by <code>--num_frames</code>. Candidate values for aspect_ratio includes <code>16:9</code>, <code>9:16</code>, <code>1:1</code>, <code>2.39:1</code>. Candidate values for num_frames should be <code>4k+1</code> and less than 129.</p> <p dir="auto">You can also run direct text-to-video by:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="# One GPU for 256px torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --prompt "raining, sea" # Multi-GPU for 768px torchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/768px.py --prompt "raining, sea""><pre><span class="pl-c"><span class="pl-c">#</span> One GPU for 256px</span> torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span> <span class="pl-c"><span class="pl-c">#</span> Multi-GPU for 768px</span> torchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/768px.py --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span></pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Image-to-Video Generation</h3><a id="user-content-image-to-video-generation" class="anchor" aria-label="Permalink: Image-to-Video Generation" href="#image-to-video-generation"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Given a prompt and a reference image, you can generate a video with the following command:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="# 256px torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --cond_type i2v_head --prompt "A plump pig wallows in a muddy pond on a rustic farm, its pink snout poking out as it snorts contentedly. The camera captures the pig's playful splashes, sending ripples through the water under the midday sun. Wooden fences and a red barn stand in the background, framed by rolling green hills. The pig's muddy coat glistens in the sunlight, showcasing the simple pleasures of its carefree life." --ref assets/texts/i2v.png # 256px with csv torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --cond_type i2v_head --dataset.data-path assets/texts/i2v.csv # Multi-GPU 768px torchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/768px.py --cond_type i2v_head --dataset.data-path assets/texts/i2v.csv"><pre><span class="pl-c"><span class="pl-c">#</span> 256px</span> torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --cond_type i2v_head --prompt <span class="pl-s"><span class="pl-pds">"</span>A plump pig wallows in a muddy pond on a rustic farm, its pink snout poking out as it snorts contentedly. The camera captures the pig's playful splashes, sending ripples through the water under the midday sun. Wooden fences and a red barn stand in the background, framed by rolling green hills. The pig's muddy coat glistens in the sunlight, showcasing the simple pleasures of its carefree life.<span class="pl-pds">"</span></span> --ref assets/texts/i2v.png <span class="pl-c"><span class="pl-c">#</span> 256px with csv</span> torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/256px.py --cond_type i2v_head --dataset.data-path assets/texts/i2v.csv <span class="pl-c"><span class="pl-c">#</span> Multi-GPU 768px</span> torchrun --nproc_per_node 8 --standalone scripts/diffusion/inference.py configs/diffusion/inference/768px.py --cond_type i2v_head --dataset.data-path assets/texts/i2v.csv</pre></div> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Advanced Usage</h2><a id="user-content-advanced-usage" class="anchor" aria-label="Permalink: Advanced Usage" href="#advanced-usage"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Motion Score</h3><a id="user-content-motion-score" class="anchor" aria-label="Permalink: Motion Score" href="#motion-score"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">During training, we provide motion score into the text prompt. During inference, you can use the following command to generate videos with motion score (the default score is 4):</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt "raining, sea" --motion-score 4"><pre>torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span> --motion-score 4</pre></div> <p dir="auto">We also provide a dynamic motion score evaluator. After setting your OpenAI API key, you can use the following command to evaluate the motion score of a video:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt "raining, sea" --motion-score dynamic"><pre>torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span> --motion-score dynamic</pre></div> <markdown-accessiblity-table><table> <thead> <tr> <th>Score</th> <th>1</th> <th>4</th> <th>7</th> </tr> </thead> <tbody> <tr> <td></td> <td><a target="_blank" rel="noopener noreferrer" href="https://github.com/hpcaitech/Open-Sora-Demo/blob/main/demo/v2.0/motion_score_1.gif"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/motion_score_1.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a target="_blank" rel="noopener noreferrer" href="https://github.com/hpcaitech/Open-Sora-Demo/blob/main/demo/v2.0/motion_score_4.gif"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/motion_score_4.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> <td><a target="_blank" rel="noopener noreferrer" href="https://github.com/hpcaitech/Open-Sora-Demo/blob/main/demo/v2.0/motion_score_7.gif"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/demo/v2.0/motion_score_7.gif" width="" data-animated-image="" style="max-width: 100%;"></a></td> </tr> </tbody> </table></markdown-accessiblity-table> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Prompt Refine</h3><a id="user-content-prompt-refine" class="anchor" aria-label="Permalink: Prompt Refine" href="#prompt-refine"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">We take advantage of ChatGPT to refine the prompt. You can use the following command to refine the prompt. The function is available for both text-to-video and image-to-video generation.</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="export OPENAI_API_KEY=sk-xxxx torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt "raining, sea" --refine-prompt True"><pre><span class="pl-k">export</span> OPENAI_API_KEY=sk-xxxx torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span> --refine-prompt True</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Reproductivity</h3><a id="user-content-reproductivity" class="anchor" aria-label="Permalink: Reproductivity" href="#reproductivity"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">To make the results reproducible, you can set the random seed by:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt "raining, sea" --sampling_option.seed 42 --seed 42"><pre>torchrun --nproc_per_node 1 --standalone scripts/diffusion/inference.py configs/diffusion/inference/t2i2v_256px.py --save-dir samples --prompt <span class="pl-s"><span class="pl-pds">"</span>raining, sea<span class="pl-pds">"</span></span> --sampling_option.seed 42 --seed 42</pre></div> <p dir="auto">Use <code>--num-sample k</code> to generate <code>k</code> samples for each prompt.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Computational Efficiency</h2><a id="user-content-computational-efficiency" class="anchor" aria-label="Permalink: Computational Efficiency" href="#computational-efficiency"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">We test the computational efficiency of text-to-video on H100/H800 GPU. For 256x256, we use colossalai's tensor parallelism, and <code>--offload True</code> is used. For 768x768, we use colossalai's sequence parallelism. All use number of steps 50. The results are presented in the format: <math-renderer class="js-inline-math" style="display: inline-block" data-static-url="https://github.githubassets.com/static" data-run-id="a63166519019d3dd05a4348534651b27">$\color{blue}{\text{Total time (s)}}/\color{red}{\text{peak GPU memory (GB)}}$</math-renderer></p> <markdown-accessiblity-table><table> <thead> <tr> <th>Resolution</th> <th>1x GPU</th> <th>2x GPUs</th> <th>4x GPUs</th> <th>8x GPUs</th> </tr> </thead> <tbody> <tr> <td>256x256</td> <td><math-renderer class="js-inline-math" style="display: inline-block" data-static-url="https://github.githubassets.com/static" data-run-id="a63166519019d3dd05a4348534651b27">$\color{blue}{60}/\color{red}{52.5}$</math-renderer></td> <td><math-renderer class="js-inline-math" style="display: inline-block" data-static-url="https://github.githubassets.com/static" data-run-id="a63166519019d3dd05a4348534651b27">$\color{blue}{40}/\color{red}{44.3}$</math-renderer></td> <td><math-renderer class="js-inline-math" style="display: inline-block" data-static-url="https://github.githubassets.com/static" data-run-id="a63166519019d3dd05a4348534651b27">$\color{blue}{34}/\color{red}{44.3}$</math-renderer></td> <td></td> </tr> <tr> <td>768x768</td> <td><math-renderer class="js-inline-math" style="display: inline-block" data-static-url="https://github.githubassets.com/static" data-run-id="a63166519019d3dd05a4348534651b27">$\color{blue}{1656}/\color{red}{60.3}$</math-renderer></td> <td><math-renderer class="js-inline-math" style="display: inline-block" data-static-url="https://github.githubassets.com/static" data-run-id="a63166519019d3dd05a4348534651b27">$\color{blue}{863}/\color{red}{48.3}$</math-renderer></td> <td><math-renderer class="js-inline-math" style="display: inline-block" data-static-url="https://github.githubassets.com/static" data-run-id="a63166519019d3dd05a4348534651b27">$\color{blue}{466}/\color{red}{44.3}$</math-renderer></td> <td><math-renderer class="js-inline-math" style="display: inline-block" data-static-url="https://github.githubassets.com/static" data-run-id="a63166519019d3dd05a4348534651b27">$\color{blue}{276}/\color{red}{44.3}$</math-renderer></td> </tr> </tbody> </table></markdown-accessiblity-table> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Evaluation</h2><a id="user-content-evaluation" class="anchor" aria-label="Permalink: Evaluation" href="#evaluation"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">On <a href="https://huggingface.co/spaces/Vchitect/VBench_Leaderboard" rel="nofollow">VBench</a>, Open-Sora 2.0 significantly narrows the gap with OpenAI’s Sora, reducing it from 4.52% → 0.69% compared to Open-Sora 1.2.</p> <p dir="auto"><a target="_blank" rel="noopener noreferrer" href="https://github.com/hpcaitech/Open-Sora-Demo/blob/main/readme/v2_vbench.png"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/readme/v2_vbench.png" alt="VBench" style="max-width: 100%;"></a></p> <p dir="auto">Human preference results show our model is on par with HunyuanVideo 11B and Step-Video 30B.</p> <p dir="auto"><a target="_blank" rel="noopener noreferrer" href="https://github.com/hpcaitech/Open-Sora-Demo/blob/main/readme/v2_winrate.png"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/readme/v2_winrate.png" alt="Win Rate" style="max-width: 100%;"></a></p> <p dir="auto">With strong performance, Open-Sora 2.0 is cost-effective.</p> <p dir="auto"><a target="_blank" rel="noopener noreferrer" href="https://github.com/hpcaitech/Open-Sora-Demo/blob/main/readme/v2_cost.png"><img src="https://github.com/hpcaitech/Open-Sora-Demo/raw/main/readme/v2_cost.png" alt="Cost" style="max-width: 100%;"></a></p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Contribution</h2><a id="user-content-contribution" class="anchor" aria-label="Permalink: Contribution" href="#contribution"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Thanks goes to these wonderful contributors:</p> <a href="https://github.com/hpcaitech/Open-Sora/graphs/contributors"> <img src="https://camo.githubusercontent.com/5cdddbfc17e31a502cd3dded290742ffb4d51dfa670ba13e6467959245f94ba4/68747470733a2f2f636f6e747269622e726f636b732f696d6167653f7265706f3d6870636169746563682f4f70656e2d536f7261" data-canonical-src="https://contrib.rocks/image?repo=hpcaitech/Open-Sora" style="max-width: 100%;"> </a> <p dir="auto">If you wish to contribute to this project, please refer to the <a href="/hpcaitech/Open-Sora/blob/main/CONTRIBUTING.md">Contribution Guideline</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Acknowledgement</h2><a id="user-content-acknowledgement" class="anchor" aria-label="Permalink: Acknowledgement" href="#acknowledgement"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Here we only list a few of the projects. For other works and datasets, please refer to our report.</p> <ul dir="auto"> <li><a href="https://github.com/hpcaitech/ColossalAI">ColossalAI</a>: A powerful large model parallel acceleration and optimization system.</li> <li><a href="https://github.com/facebookresearch/DiT">DiT</a>: Scalable Diffusion Models with Transformers.</li> <li><a href="https://github.com/NUS-HPC-AI-Lab/OpenDiT">OpenDiT</a>: An acceleration for DiT training. We adopt valuable acceleration strategies for training progress from OpenDiT.</li> <li><a href="https://github.com/PixArt-alpha/PixArt-alpha">PixArt</a>: An open-source DiT-based text-to-image model.</li> <li><a href="https://github.com/black-forest-labs/flux">Flux</a>: A powerful text-to-image generation model.</li> <li><a href="https://github.com/Vchitect/Latte">Latte</a>: An attempt to efficiently train DiT for video.</li> <li><a href="https://github.com/Tencent/HunyuanVideo/tree/main?tab=readme-ov-file">HunyuanVideo</a>: Open-Source text-to-video model.</li> <li><a href="https://huggingface.co/stabilityai/sd-vae-ft-mse-original" rel="nofollow">StabilityAI VAE</a>: A powerful image VAE model.</li> <li><a href="https://github.com/mit-han-lab/efficientvit">DC-AE</a>: Deep Compression AutoEncoder for image compression.</li> <li><a href="https://github.com/openai/CLIP">CLIP</a>: A powerful text-image embedding model.</li> <li><a href="https://github.com/google-research/text-to-text-transfer-transformer">T5</a>: A powerful text encoder.</li> <li><a href="https://github.com/haotian-liu/LLaVA">LLaVA</a>: A powerful image captioning model based on <a href="https://huggingface.co/mistralai/Mistral-7B-v0.1" rel="nofollow">Mistral-7B</a> and <a href="https://huggingface.co/01-ai/Yi-34B" rel="nofollow">Yi-34B</a>.</li> <li><a href="https://github.com/magic-research/PLLaVA">PLLaVA</a>: A powerful video captioning model.</li> <li><a href="https://github.com/mira-space/MiraData">MiraData</a>: A large-scale video dataset with long durations and structured caption.</li> </ul> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Citation</h2><a id="user-content-citation" class="anchor" aria-label="Permalink: Citation" href="#citation"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="highlight highlight-text-bibtex notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="@article{opensora, title={Open-sora: Democratizing efficient video production for all}, author={Zheng, Zangwei and Peng, Xiangyu and Yang, Tianji and Shen, Chenhui and Li, Shenggui and Liu, Hongxin and Zhou, Yukun and Li, Tianyi and You, Yang}, journal={arXiv preprint arXiv:2412.20404}, year={2024} } @article{opensora2, title={Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k}, author={Xiangyu Peng and Zangwei Zheng and Chenhui Shen and Tom Young and Xinying Guo and Binluo Wang and Hang Xu and Hongxin Liu and Mingyan Jiang and Wenjun Li and Yuhui Wang and Anbang Ye and Gang Ren and Qianran Ma and Wanying Liang and Xiang Lian and Xiwen Wu and Yuting Zhong and Zhuangyan Li and Chaoyu Gong and Guojun Lei and Leijun Cheng and Limin Zhang and Minghao Li and Ruijie Zhang and Silan Hu and Shijie Huang and Xiaokang Wang and Yuanheng Zhao and Yuqi Wang and Ziang Wei and Yang You}, year={2025}, journal={arXiv preprint arXiv:2503.09642}, }"><pre><span class="pl-k">@article</span>{<span class="pl-en">opensora</span>, <span class="pl-s">title</span>=<span class="pl-s"><span class="pl-pds">{</span>Open-sora: Democratizing efficient video production for all<span class="pl-pds">}</span></span>, <span class="pl-s">author</span>=<span class="pl-s"><span class="pl-pds">{</span>Zheng, Zangwei and Peng, Xiangyu and Yang, Tianji and Shen, Chenhui and Li, Shenggui and Liu, Hongxin and Zhou, Yukun and Li, Tianyi and You, Yang<span class="pl-pds">}</span></span>, <span class="pl-s">journal</span>=<span class="pl-s"><span class="pl-pds">{</span>arXiv preprint arXiv:2412.20404<span class="pl-pds">}</span></span>, <span class="pl-s">year</span>=<span class="pl-s"><span class="pl-pds">{</span>2024<span class="pl-pds">}</span></span> } <span class="pl-k">@article</span>{<span class="pl-en">opensora2</span>, <span class="pl-s">title</span>=<span class="pl-s"><span class="pl-pds">{</span>Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k<span class="pl-pds">}</span></span>, <span class="pl-s">author</span>=<span class="pl-s"><span class="pl-pds">{</span>Xiangyu Peng and Zangwei Zheng and Chenhui Shen and Tom Young and Xinying Guo and Binluo Wang and Hang Xu and Hongxin Liu and Mingyan Jiang and Wenjun Li and Yuhui Wang and Anbang Ye and Gang Ren and Qianran Ma and Wanying Liang and Xiang Lian and Xiwen Wu and Yuting Zhong and Zhuangyan Li and Chaoyu Gong and Guojun Lei and Leijun Cheng and Limin Zhang and Minghao Li and Ruijie Zhang and Silan Hu and Shijie Huang and Xiaokang Wang and Yuanheng Zhao and Yuqi Wang and Ziang Wei and Yang You<span class="pl-pds">}</span></span>, <span class="pl-s">year</span>=<span class="pl-s"><span class="pl-pds">{</span>2025<span class="pl-pds">}</span></span>, <span class="pl-s">journal</span>=<span class="pl-s"><span class="pl-pds">{</span>arXiv preprint arXiv:2503.09642<span class="pl-pds">}</span></span>, }</pre></div> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Star History</h2><a id="user-content-star-history" class="anchor" aria-label="Permalink: Star History" href="#star-history"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><a href="https://star-history.com/#hpcaitech/Open-Sora&Date" rel="nofollow"><img src="https://camo.githubusercontent.com/3fe4ff7323fb8ded741d90823b8c8937c6f43e029539c3ca8721a70f0bd1fc2e/68747470733a2f2f6170692e737461722d686973746f72792e636f6d2f7376673f7265706f733d6870636169746563682f4f70656e2d536f726126747970653d44617465" alt="Star History Chart" data-canonical-src="https://api.star-history.com/svg?repos=hpcaitech/Open-Sora&type=Date" style="max-width: 100%;"></a></p> </article></div></div></div></div></div> 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<strong>2.5k</strong> forks</a> </div> <div class="mt-2"> <a class="Link--muted" href="/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2Fhpcaitech%2FOpen-Sora&report=hpcaitech+%28user%29"> Report repository </a> </div> </div> </div> </div> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <h2 class="h4 mb-3" data-pjax="#repo-content-pjax-container" data-turbo-frame="repo-content-turbo-frame"> <a href="/hpcaitech/Open-Sora/releases" data-view-component="true" class="Link--primary no-underline Link">Releases <span title="4" data-view-component="true" class="Counter">4</span></a></h2> <a class="Link--primary d-flex no-underline" data-pjax="#repo-content-pjax-container" data-turbo-frame="repo-content-turbo-frame" href="/hpcaitech/Open-Sora/releases/tag/v1.3"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-tag flex-shrink-0 mt-1 color-fg-success"> <path d="M1 7.775V2.75C1 1.784 1.784 1 2.75 1h5.025c.464 0 .91.184 1.238.513l6.25 6.25a1.75 1.75 0 0 1 0 2.474l-5.026 5.026a1.75 1.75 0 0 1-2.474 0l-6.25-6.25A1.752 1.752 0 0 1 1 7.775Zm1.5 0c0 .066.026.13.073.177l6.25 6.25a.25.25 0 0 0 .354 0l5.025-5.025a.25.25 0 0 0 0-.354l-6.25-6.25a.25.25 0 0 0-.177-.073H2.75a.25.25 0 0 0-.25.25ZM6 5a1 1 0 1 1 0 2 1 1 0 0 1 0-2Z"></path> </svg> <div class="ml-2 min-width-0"> <div class="d-flex"> <span class="css-truncate css-truncate-target text-bold mr-2" style="max-width: none;">Open-Sora V1.3 Release</span> <span title="Label: Latest" data-view-component="true" class="Label Label--success flex-shrink-0"> Latest </span> </div> <div class="text-small color-fg-muted"><relative-time datetime="2025-02-21T02:30:05Z" class="no-wrap">Feb 21, 2025</relative-time></div> </div> </a> <div data-view-component="true" class="mt-3"> <a text="small" data-pjax="#repo-content-pjax-container" data-turbo-frame="repo-content-turbo-frame" href="/hpcaitech/Open-Sora/releases" data-view-component="true" 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class="list-style-none d-flex flex-wrap mb-n2"> <li class="mb-2 mr-2" > <a href="https://github.com/zhengzangw" class="" data-hovercard-type="user" data-hovercard-url="/users/zhengzangw/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/30647653?s=64&v=4" alt="@zhengzangw" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/Shen-Chenhui" class="" data-hovercard-type="user" data-hovercard-url="/users/Shen-Chenhui/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/24800477?s=64&v=4" alt="@Shen-Chenhui" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/FrankLeeeee" class="" data-hovercard-type="user" data-hovercard-url="/users/FrankLeeeee/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/31818963?s=64&v=4" alt="@FrankLeeeee" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/tomyoung903" class="" data-hovercard-type="user" data-hovercard-url="/users/tomyoung903/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/44153440?s=64&v=4" alt="@tomyoung903" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/xyupeng" class="" data-hovercard-type="user" data-hovercard-url="/users/xyupeng/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/99191637?s=64&v=4" alt="@xyupeng" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/Yanjia0" class="" data-hovercard-type="user" data-hovercard-url="/users/Yanjia0/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/42895286?s=64&v=4" alt="@Yanjia0" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/ver217" class="" data-hovercard-type="user" data-hovercard-url="/users/ver217/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/23111350?s=64&v=4" alt="@ver217" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/Sze-qq" class="" data-hovercard-type="user" data-hovercard-url="/users/Sze-qq/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/68757353?s=64&v=4" alt="@Sze-qq" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/1zeryu" class="" data-hovercard-type="user" data-hovercard-url="/users/1zeryu/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/90625606?s=64&v=4" alt="@1zeryu" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/binmakeswell" class="" data-hovercard-type="user" data-hovercard-url="/users/binmakeswell/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/61670638?s=64&v=4" alt="@binmakeswell" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/eltociear" class="" data-hovercard-type="user" data-hovercard-url="/users/eltociear/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/22633385?s=64&v=4" alt="@eltociear" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/gxyes" class="" data-hovercard-type="user" data-hovercard-url="/users/gxyes/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/96687844?s=64&v=4" alt="@gxyes" size="32" height="32" width="32" data-view-component="true" 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0v-2.5a.75.75 0 0 1 1.5 0ZM9 11a1 1 0 1 1-2 0 1 1 0 0 1 2 0Z"></path> </svg> <button type="button" class="flash-close js-ajax-error-dismiss" aria-label="Dismiss error"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-x"> <path d="M3.72 3.72a.75.75 0 0 1 1.06 0L8 6.94l3.22-3.22a.749.749 0 0 1 1.275.326.749.749 0 0 1-.215.734L9.06 8l3.22 3.22a.749.749 0 0 1-.326 1.275.749.749 0 0 1-.734-.215L8 9.06l-3.22 3.22a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042L6.94 8 3.72 4.78a.75.75 0 0 1 0-1.06Z"></path> </svg> </button> You can’t perform that action at this time. </div> <template id="site-details-dialog"> <details class="details-reset details-overlay details-overlay-dark lh-default color-fg-default hx_rsm" open> <summary role="button" aria-label="Close dialog"></summary> <details-dialog class="Box Box--overlay d-flex flex-column anim-fade-in fast hx_rsm-dialog hx_rsm-modal"> <button class="Box-btn-octicon m-0 btn-octicon position-absolute right-0 top-0" type="button" aria-label="Close dialog" data-close-dialog> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-x"> <path d="M3.72 3.72a.75.75 0 0 1 1.06 0L8 6.94l3.22-3.22a.749.749 0 0 1 1.275.326.749.749 0 0 1-.215.734L9.06 8l3.22 3.22a.749.749 0 0 1-.326 1.275.749.749 0 0 1-.734-.215L8 9.06l-3.22 3.22a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042L6.94 8 3.72 4.78a.75.75 0 0 1 0-1.06Z"></path> </svg> </button> <div class="octocat-spinner my-6 js-details-dialog-spinner"></div> </details-dialog> </details> </template> <div class="Popover js-hovercard-content position-absolute" style="display: none; outline: none;"> <div class="Popover-message Popover-message--bottom-left Popover-message--large Box color-shadow-large" style="width:360px;"> </div> </div> <template id="snippet-clipboard-copy-button"> <div class="zeroclipboard-container position-absolute right-0 top-0"> <clipboard-copy aria-label="Copy" class="ClipboardButton btn js-clipboard-copy m-2 p-0" data-copy-feedback="Copied!" data-tooltip-direction="w"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-copy js-clipboard-copy-icon m-2"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 0 1 0 1.5h-1.5a.25.25 0 0 0-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 0 0 .25-.25v-1.5a.75.75 0 0 1 1.5 0v1.5A1.75 1.75 0 0 1 9.25 16h-7.5A1.75 1.75 0 0 1 0 14.25Z"></path><path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0 1 14.25 11h-7.5A1.75 1.75 0 0 1 5 9.25Zm1.75-.25a.25.25 0 0 0-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 0 0 .25-.25v-7.5a.25.25 0 0 0-.25-.25Z"></path> </svg> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-check js-clipboard-check-icon color-fg-success d-none m-2"> <path d="M13.78 4.22a.75.75 0 0 1 0 1.06l-7.25 7.25a.75.75 0 0 1-1.06 0L2.22 9.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018L6 10.94l6.72-6.72a.75.75 0 0 1 1.06 0Z"></path> </svg> </clipboard-copy> </div> </template> <template id="snippet-clipboard-copy-button-unpositioned"> <div class="zeroclipboard-container"> <clipboard-copy aria-label="Copy" class="ClipboardButton btn btn-invisible js-clipboard-copy m-2 p-0 d-flex flex-justify-center flex-items-center" data-copy-feedback="Copied!" data-tooltip-direction="w"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-copy js-clipboard-copy-icon"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 0 1 0 1.5h-1.5a.25.25 0 0 0-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 0 0 .25-.25v-1.5a.75.75 0 0 1 1.5 0v1.5A1.75 1.75 0 0 1 9.25 16h-7.5A1.75 1.75 0 0 1 0 14.25Z"></path><path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0 1 14.25 11h-7.5A1.75 1.75 0 0 1 5 9.25Zm1.75-.25a.25.25 0 0 0-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 0 0 .25-.25v-7.5a.25.25 0 0 0-.25-.25Z"></path> </svg> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-check js-clipboard-check-icon color-fg-success d-none"> <path d="M13.78 4.22a.75.75 0 0 1 0 1.06l-7.25 7.25a.75.75 0 0 1-1.06 0L2.22 9.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018L6 10.94l6.72-6.72a.75.75 0 0 1 1.06 0Z"></path> </svg> </clipboard-copy> </div> </template> </div> <div id="js-global-screen-reader-notice" class="sr-only mt-n1" aria-live="polite" aria-atomic="true" ></div> <div id="js-global-screen-reader-notice-assertive" class="sr-only mt-n1" aria-live="assertive" aria-atomic="true"></div> </body> </html>