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dir=\"auto\"\u003eTriton Inference Server\u003c/h1\u003e\u003ca id=\"user-content-triton-inference-server\" class=\"anchor\" aria-label=\"Permalink: Triton Inference Server\" href=\"#triton-inference-server\"\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://opensource.org/licenses/BSD-3-Clause\" rel=\"nofollow\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/f7da0c60c3c35540f74d75a8003ca2f306dd5d9db99a534a5ec3e1e6b80150c6/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f4c6963656e73652d425344332d6c69676874677265792e737667\" alt=\"License\" data-canonical-src=\"https://img.shields.io/badge/License-BSD3-lightgrey.svg\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cdiv class=\"markdown-alert markdown-alert-warning\" dir=\"auto\"\u003e\u003cp class=\"markdown-alert-title\" dir=\"auto\"\u003e\u003csvg class=\"octicon octicon-alert mr-2\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"M6.457 1.047c.659-1.234 2.427-1.234 3.086 0l6.082 11.378A1.75 1.75 0 0 1 14.082 15H1.918a1.75 1.75 0 0 1-1.543-2.575Zm1.763.707a.25.25 0 0 0-.44 0L1.698 13.132a.25.25 0 0 0 .22.368h12.164a.25.25 0 0 0 .22-.368Zm.53 3.996v2.5a.75.75 0 0 1-1.5 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\"\u003e\u003c/path\u003e\u003c/svg\u003eWarning\u003c/p\u003e\u003cp dir=\"auto\"\u003eYou are currently on the \u003ccode\u003emain\u003c/code\u003e branch which tracks under-development progress\ntowards the next release. The current release is version \u003ca href=\"https://github.com/triton-inference-server/server/releases/latest\"\u003e2.52.0\u003c/a\u003e\nand corresponds to the 24.11 container release on NVIDIA GPU Cloud (NGC).\u003c/p\u003e\n\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eTriton Inference Server is an open source inference serving software that\nstreamlines AI inferencing. Triton enables teams to deploy any AI model from\nmultiple deep learning and machine learning frameworks, including TensorRT,\nTensorFlow, PyTorch, ONNX, OpenVINO, Python, RAPIDS FIL, and more. Triton\nInference Server supports inference across cloud, data center, edge and embedded\ndevices on NVIDIA GPUs, x86 and ARM CPU, or AWS Inferentia. Triton Inference\nServer delivers optimized performance for many query types, including real time,\nbatched, ensembles and audio/video streaming. Triton inference Server is part of\n\u003ca href=\"https://www.nvidia.com/en-us/data-center/products/ai-enterprise/\" rel=\"nofollow\"\u003eNVIDIA AI Enterprise\u003c/a\u003e,\na software platform that accelerates the data science pipeline and streamlines\nthe development and deployment of production AI.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eMajor features include:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/triton-inference-server/backend#where-can-i-find-all-the-backends-that-are-available-for-triton\"\u003eSupports multiple deep learning\nframeworks\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/triton-inference-server/fil_backend\"\u003eSupports multiple machine learning\nframeworks\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#concurrent-model-execution\"\u003eConcurrent model\nexecution\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#dynamic-batcher\"\u003eDynamic batching\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#sequence-batcher\"\u003eSequence batching\u003c/a\u003e and\n\u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#implicit-state-management\"\u003eimplicit state management\u003c/a\u003e\nfor stateful models\u003c/li\u003e\n\u003cli\u003eProvides \u003ca href=\"https://github.com/triton-inference-server/backend\"\u003eBackend API\u003c/a\u003e that\nallows adding custom backends and pre/post processing operations\u003c/li\u003e\n\u003cli\u003eSupports writing custom backends in python, a.k.a.\n\u003ca href=\"https://github.com/triton-inference-server/backend/blob/main/docs/python_based_backends.md#python-based-backends\"\u003ePython-based backends.\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eModel pipelines using\n\u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#ensemble-models\"\u003eEnsembling\u003c/a\u003e or \u003ca href=\"https://github.com/triton-inference-server/python_backend#business-logic-scripting\"\u003eBusiness\nLogic Scripting\n(BLS)\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/inference_protocols.md\"\u003eHTTP/REST and GRPC inference\nprotocols\u003c/a\u003e based on the community\ndeveloped \u003ca href=\"https://github.com/kserve/kserve/tree/master/docs/predict-api/v2\"\u003eKServe\nprotocol\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eA \u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/inference_protocols.md#in-process-triton-server-api\"\u003eC API\u003c/a\u003e and\n\u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/inference_protocols.md#java-bindings-for-in-process-triton-server-api\"\u003eJava API\u003c/a\u003e\nallow Triton to link directly into your application for edge and other in-process use cases\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/metrics.md\"\u003eMetrics\u003c/a\u003e indicating GPU utilization, server\nthroughput, server latency, and more\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eNew to Triton Inference Server?\u003c/strong\u003e Make use of\n\u003ca href=\"https://github.com/triton-inference-server/tutorials\"\u003ethese tutorials\u003c/a\u003e\nto begin your Triton journey!\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eJoin the \u003ca href=\"https://www.nvidia.com/en-us/deep-learning-ai/triton-tensorrt-newsletter/\" rel=\"nofollow\"\u003eTriton and TensorRT community\u003c/a\u003e and\nstay current on the latest product updates, bug fixes, content, best practices,\nand more. Need enterprise support? NVIDIA global support is available for Triton\nInference Server with the\n\u003ca href=\"https://www.nvidia.com/en-us/data-center/products/ai-enterprise/\" rel=\"nofollow\"\u003eNVIDIA AI Enterprise software suite\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eServe a Model in 3 Easy Steps\u003c/h2\u003e\u003ca id=\"user-content-serve-a-model-in-3-easy-steps\" class=\"anchor\" aria-label=\"Permalink: Serve a Model in 3 Easy Steps\" href=\"#serve-a-model-in-3-easy-steps\"\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=\"# Step 1: Create the example model repository\ngit clone -b r24.11 https://github.com/triton-inference-server/server.git\ncd server/docs/examples\n./fetch_models.sh\n\n# Step 2: Launch triton from the NGC Triton container\ndocker run --gpus=1 --rm --net=host -v ${PWD}/model_repository:/models nvcr.io/nvidia/tritonserver:24.11-py3 tritonserver --model-repository=/models\n\n# Step 3: Sending an Inference Request\n# In a separate console, launch the image_client example from the NGC Triton SDK container\ndocker run -it --rm --net=host nvcr.io/nvidia/tritonserver:24.11-py3-sdk\n/workspace/install/bin/image_client -m densenet_onnx -c 3 -s INCEPTION /workspace/images/mug.jpg\n\n# Inference should return the following\nImage '/workspace/images/mug.jpg':\n 15.346230 (504) = COFFEE MUG\n 13.224326 (968) = CUP\n 10.422965 (505) = COFFEEPOT\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Step 1: Create the example model repository\u003c/span\u003e\ngit clone -b r24.11 https://github.com/triton-inference-server/server.git\n\u003cspan class=\"pl-c1\"\u003ecd\u003c/span\u003e server/docs/examples\n./fetch_models.sh\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Step 2: Launch triton from the NGC Triton container\u003c/span\u003e\ndocker run --gpus=1 --rm --net=host -v \u003cspan class=\"pl-smi\"\u003e${PWD}\u003c/span\u003e/model_repository:/models nvcr.io/nvidia/tritonserver:24.11-py3 tritonserver --model-repository=/models\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Step 3: Sending an Inference Request\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e In a separate console, launch the image_client example from the NGC Triton SDK container\u003c/span\u003e\ndocker run -it --rm --net=host nvcr.io/nvidia/tritonserver:24.11-py3-sdk\n/workspace/install/bin/image_client -m densenet_onnx -c 3 -s INCEPTION /workspace/images/mug.jpg\n\n\u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e Inference should return the following\u003c/span\u003e\nImage \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e'\u003c/span\u003e/workspace/images/mug.jpg\u003cspan class=\"pl-pds\"\u003e'\u003c/span\u003e\u003c/span\u003e:\n 15.346230 (504) = COFFEE MUG\n 13.224326 (968) = CUP\n 10.422965 (505) = COFFEEPOT\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003ePlease read the \u003ca href=\"/triton-inference-server/server/blob/main/docs/getting_started/quickstart.md\"\u003eQuickStart\u003c/a\u003e guide for additional information\nregarding this example. The quickstart guide also contains an example of how to launch Triton on \u003ca href=\"/triton-inference-server/server/blob/main/docs/getting_started/quickstart.md#run-on-cpu-only-system\"\u003eCPU-only systems\u003c/a\u003e. New to Triton and wondering where to get started? Watch the \u003ca href=\"https://youtu.be/NQDtfSi5QF4\" rel=\"nofollow\"\u003eGetting Started video\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eExamples and Tutorials\u003c/h2\u003e\u003ca id=\"user-content-examples-and-tutorials\" class=\"anchor\" aria-label=\"Permalink: Examples and Tutorials\" href=\"#examples-and-tutorials\"\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\"\u003eCheck out \u003ca href=\"https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/trial/\" rel=\"nofollow\"\u003eNVIDIA LaunchPad\u003c/a\u003e\nfor free access to a set of hands-on labs with Triton Inference Server hosted on\nNVIDIA infrastructure.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eSpecific end-to-end examples for popular models, such as ResNet, BERT, and DLRM\nare located in the\n\u003ca href=\"https://github.com/NVIDIA/DeepLearningExamples\"\u003eNVIDIA Deep Learning Examples\u003c/a\u003e\npage on GitHub. The\n\u003ca href=\"https://developer.nvidia.com/nvidia-triton-inference-server\" rel=\"nofollow\"\u003eNVIDIA Developer Zone\u003c/a\u003e\ncontains additional documentation, presentations, and examples.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eDocumentation\u003c/h2\u003e\u003ca id=\"user-content-documentation\" class=\"anchor\" aria-label=\"Permalink: Documentation\" href=\"#documentation\"\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\"\u003eBuild and Deploy\u003c/h3\u003e\u003ca id=\"user-content-build-and-deploy\" class=\"anchor\" aria-label=\"Permalink: Build and Deploy\" href=\"#build-and-deploy\"\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\"\u003eThe recommended way to build and use Triton Inference Server is with Docker\nimages.\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/build.md#building-with-docker\"\u003eInstall Triton Inference Server with Docker containers\u003c/a\u003e (\u003cem\u003eRecommended\u003c/em\u003e)\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/build.md#building-without-docker\"\u003eInstall Triton Inference Server without Docker containers\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/compose.md\"\u003eBuild a custom Triton Inference Server Docker container\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/build.md#building-on-unsupported-platforms\"\u003eBuild Triton Inference Server from source\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/build.md#building-for-windows-10\"\u003eBuild Triton Inference Server for Windows 10\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eExamples for deploying Triton Inference Server with Kubernetes and Helm on \u003ca href=\"/triton-inference-server/server/blob/main/deploy/gcp/README.md\"\u003eGCP\u003c/a\u003e,\n\u003ca href=\"/triton-inference-server/server/blob/main/deploy/aws/README.md\"\u003eAWS\u003c/a\u003e, and \u003ca href=\"/triton-inference-server/server/blob/main/deploy/fleetcommand/README.md\"\u003eNVIDIA FleetCommand\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/deploy.md\"\u003eSecure Deployment Considerations\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eUsing Triton\u003c/h3\u003e\u003ca id=\"user-content-using-triton\" class=\"anchor\" aria-label=\"Permalink: Using Triton\" href=\"#using-triton\"\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\u003ch4 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003ePreparing Models for Triton Inference Server\u003c/h4\u003e\u003ca id=\"user-content-preparing-models-for-triton-inference-server\" class=\"anchor\" aria-label=\"Permalink: Preparing Models for Triton Inference Server\" href=\"#preparing-models-for-triton-inference-server\"\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\"\u003eThe first step in using Triton to serve your models is to place one or\nmore models into a \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/model_repository.md\"\u003emodel repository\u003c/a\u003e. Depending on\nthe type of the model and on what Triton capabilities you want to enable for\nthe model, you may need to create a \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md\"\u003emodel\nconfiguration\u003c/a\u003e for the model.\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/custom_operations.md\"\u003eAdd custom operations to Triton if needed by your model\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eEnable model pipelining with \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#ensemble-models\"\u003eModel Ensemble\u003c/a\u003e\nand \u003ca href=\"https://github.com/triton-inference-server/python_backend#business-logic-scripting\"\u003eBusiness Logic Scripting (BLS)\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eOptimize your models setting \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#models-and-schedulers\"\u003escheduling and batching\u003c/a\u003e\nparameters and \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#instance-groups\"\u003emodel instances\u003c/a\u003e.\u003c/li\u003e\n\u003cli\u003eUse the \u003ca href=\"https://github.com/triton-inference-server/model_analyzer\"\u003eModel Analyzer tool\u003c/a\u003e\nto help optimize your model configuration with profiling\u003c/li\u003e\n\u003cli\u003eLearn how to \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/model_management.md\"\u003eexplicitly manage what models are available by loading and\nunloading models\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch4 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eConfigure and Use Triton Inference Server\u003c/h4\u003e\u003ca id=\"user-content-configure-and-use-triton-inference-server\" class=\"anchor\" aria-label=\"Permalink: Configure and Use Triton Inference Server\" href=\"#configure-and-use-triton-inference-server\"\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\u003eRead the \u003ca href=\"/triton-inference-server/server/blob/main/docs/getting_started/quickstart.md\"\u003eQuick Start Guide\u003c/a\u003e to run Triton Inference\nServer on both GPU and CPU\u003c/li\u003e\n\u003cli\u003eTriton supports multiple execution engines, called\n\u003ca href=\"https://github.com/triton-inference-server/backend#where-can-i-find-all-the-backends-that-are-available-for-triton\"\u003ebackends\u003c/a\u003e, including\n\u003ca href=\"https://github.com/triton-inference-server/tensorrt_backend\"\u003eTensorRT\u003c/a\u003e,\n\u003ca href=\"https://github.com/triton-inference-server/tensorflow_backend\"\u003eTensorFlow\u003c/a\u003e,\n\u003ca href=\"https://github.com/triton-inference-server/pytorch_backend\"\u003ePyTorch\u003c/a\u003e,\n\u003ca href=\"https://github.com/triton-inference-server/onnxruntime_backend\"\u003eONNX\u003c/a\u003e,\n\u003ca href=\"https://github.com/triton-inference-server/openvino_backend\"\u003eOpenVINO\u003c/a\u003e,\n\u003ca href=\"https://github.com/triton-inference-server/python_backend\"\u003ePython\u003c/a\u003e, and more\u003c/li\u003e\n\u003cli\u003eNot all the above backends are supported on every platform supported by Triton.\nLook at the\n\u003ca href=\"https://github.com/triton-inference-server/backend/blob/main/docs/backend_platform_support_matrix.md\"\u003eBackend-Platform Support Matrix\u003c/a\u003e\nto learn which backends are supported on your target platform.\u003c/li\u003e\n\u003cli\u003eLearn how to \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/optimization.md\"\u003eoptimize performance\u003c/a\u003e using the\n\u003ca href=\"https://github.com/triton-inference-server/perf_analyzer/blob/main/README.md\"\u003ePerformance Analyzer\u003c/a\u003e\nand\n\u003ca href=\"https://github.com/triton-inference-server/model_analyzer\"\u003eModel Analyzer\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eLearn how to \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/model_management.md\"\u003emanage loading and unloading models\u003c/a\u003e in\nTriton\u003c/li\u003e\n\u003cli\u003eSend requests directly to Triton with the \u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/inference_protocols.md#httprest-and-grpc-protocols\"\u003eHTTP/REST JSON-based\nor gRPC protocols\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch4 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eClient Support and Examples\u003c/h4\u003e\u003ca id=\"user-content-client-support-and-examples\" class=\"anchor\" aria-label=\"Permalink: Client Support and Examples\" href=\"#client-support-and-examples\"\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\"\u003eA Triton \u003cem\u003eclient\u003c/em\u003e application sends inference and other requests to Triton. The\n\u003ca href=\"https://github.com/triton-inference-server/client\"\u003ePython and C++ client libraries\u003c/a\u003e\nprovide APIs to simplify this communication.\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eReview client examples for \u003ca href=\"https://github.com/triton-inference-server/client/blob/main/src/c%2B%2B/examples\"\u003eC++\u003c/a\u003e,\n\u003ca href=\"https://github.com/triton-inference-server/client/blob/main/src/python/examples\"\u003ePython\u003c/a\u003e,\nand \u003ca href=\"https://github.com/triton-inference-server/client/blob/main/src/java/src/main/java/triton/client/examples\"\u003eJava\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eConfigure \u003ca href=\"https://github.com/triton-inference-server/client#http-options\"\u003eHTTP\u003c/a\u003e\nand \u003ca href=\"https://github.com/triton-inference-server/client#grpc-options\"\u003egRPC\u003c/a\u003e\nclient options\u003c/li\u003e\n\u003cli\u003eSend input data (e.g. a jpeg image) directly to Triton in the \u003ca href=\"https://github.com/triton-inference-server/server/blob/main/docs/protocol/extension_binary_data.md#raw-binary-request\"\u003ebody of an HTTP\nrequest without any additional metadata\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eExtend Triton\u003c/h3\u003e\u003ca id=\"user-content-extend-triton\" class=\"anchor\" aria-label=\"Permalink: Extend Triton\" href=\"#extend-triton\"\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=\"/triton-inference-server/server/blob/main/docs/user_guide/architecture.md\"\u003eTriton Inference Server's architecture\u003c/a\u003e is specifically\ndesigned for modularity and flexibility\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/compose.md\"\u003eCustomize Triton Inference Server container\u003c/a\u003e for your use case\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/triton-inference-server/backend\"\u003eCreate custom backends\u003c/a\u003e\nin either \u003ca href=\"https://github.com/triton-inference-server/backend/blob/main/README.md#triton-backend-api\"\u003eC/C++\u003c/a\u003e\nor \u003ca href=\"https://github.com/triton-inference-server/python_backend\"\u003ePython\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eCreate \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/decoupled_models.md\"\u003edecoupled backends and models\u003c/a\u003e that can send\nmultiple responses for a request or not send any responses for a request\u003c/li\u003e\n\u003cli\u003eUse a \u003ca href=\"/triton-inference-server/server/blob/main/docs/customization_guide/repository_agents.md\"\u003eTriton repository agent\u003c/a\u003e to add functionality\nthat operates when a model is loaded and unloaded, such as authentication,\ndecryption, or conversion\u003c/li\u003e\n\u003cli\u003eDeploy Triton on \u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/jetson.md\"\u003eJetson and JetPack\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/triton-inference-server/python_backend/tree/main/inferentia\"\u003eUse Triton on AWS\nInferentia\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eAdditional Documentation\u003c/h3\u003e\u003ca id=\"user-content-additional-documentation\" class=\"anchor\" aria-label=\"Permalink: Additional Documentation\" href=\"#additional-documentation\"\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\u003ca href=\"/triton-inference-server/server/blob/main/docs/user_guide/faq.md\"\u003eFAQ\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/README.md#user-guide\"\u003eUser Guide\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/triton-inference-server/server/blob/main/docs/README.md#customization-guide\"\u003eCustomization Guide\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://docs.nvidia.com/deeplearning/triton-inference-server/release-notes/index.html\" rel=\"nofollow\"\u003eRelease Notes\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://docs.nvidia.com/deeplearning/dgx/support-matrix/index.html\" rel=\"nofollow\"\u003eGPU, Driver, and CUDA Support\nMatrix\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eContributing\u003c/h2\u003e\u003ca id=\"user-content-contributing\" class=\"anchor\" aria-label=\"Permalink: Contributing\" href=\"#contributing\"\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\"\u003eContributions to Triton Inference Server are more than welcome. To\ncontribute please review the \u003ca href=\"/triton-inference-server/server/blob/main/CONTRIBUTING.md\"\u003econtribution\nguidelines\u003c/a\u003e. If you have a backend, client,\nexample or similar contribution that is not modifying the core of\nTriton, then you should file a PR in the \u003ca href=\"https://github.com/triton-inference-server/contrib\"\u003econtrib\nrepo\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eReporting problems, asking questions\u003c/h2\u003e\u003ca id=\"user-content-reporting-problems-asking-questions\" class=\"anchor\" aria-label=\"Permalink: Reporting problems, asking questions\" href=\"#reporting-problems-asking-questions\"\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 appreciate any feedback, questions or bug reporting regarding this project.\nWhen posting \u003ca href=\"https://github.com/triton-inference-server/server/issues\"\u003eissues in GitHub\u003c/a\u003e,\nfollow the process outlined in the \u003ca href=\"https://stackoverflow.com/help/mcve\" rel=\"nofollow\"\u003eStack Overflow document\u003c/a\u003e.\nEnsure posted examples are:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eminimal – use as little code as possible that still produces the\nsame problem\u003c/li\u003e\n\u003cli\u003ecomplete – provide all parts needed to reproduce the problem. Check\nif you can strip external dependencies and still show the problem. The\nless time we spend on reproducing problems the more time we have to\nfix it\u003c/li\u003e\n\u003cli\u003everifiable – test the code you're about to provide to make sure it\nreproduces the problem. Remove all other problems that are not\nrelated to your request/question.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003eFor issues, please use the provided bug report and feature request templates.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eFor questions, we recommend posting in our community\n\u003ca href=\"https://github.com/triton-inference-server/server/discussions\"\u003eGitHub Discussions.\u003c/a\u003e\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eFor more information\u003c/h2\u003e\u003ca id=\"user-content-for-more-information\" class=\"anchor\" aria-label=\"Permalink: For more information\" href=\"#for-more-information\"\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\"\u003ePlease refer to the \u003ca href=\"https://developer.nvidia.com/nvidia-triton-inference-server\" rel=\"nofollow\"\u003eNVIDIA Developer Triton page\u003c/a\u003e\nfor more information.\u003c/p\u003e\n\u003c/article\u003e","loaded":true,"timedOut":false,"errorMessage":null,"headerInfo":{"toc":[{"level":1,"text":"Triton Inference Server","anchor":"triton-inference-server","htmlText":"Triton Inference Server"},{"level":2,"text":"Serve a Model in 3 Easy Steps","anchor":"serve-a-model-in-3-easy-steps","htmlText":"Serve a Model in 3 Easy Steps"},{"level":2,"text":"Examples and Tutorials","anchor":"examples-and-tutorials","htmlText":"Examples and Tutorials"},{"level":2,"text":"Documentation","anchor":"documentation","htmlText":"Documentation"},{"level":3,"text":"Build and Deploy","anchor":"build-and-deploy","htmlText":"Build and Deploy"},{"level":3,"text":"Using Triton","anchor":"using-triton","htmlText":"Using Triton"},{"level":4,"text":"Preparing Models for Triton Inference Server","anchor":"preparing-models-for-triton-inference-server","htmlText":"Preparing Models for Triton Inference Server"},{"level":4,"text":"Configure and Use Triton Inference Server","anchor":"configure-and-use-triton-inference-server","htmlText":"Configure and Use Triton Inference Server"},{"level":4,"text":"Client Support and Examples","anchor":"client-support-and-examples","htmlText":"Client Support and Examples"},{"level":3,"text":"Extend Triton","anchor":"extend-triton","htmlText":"Extend Triton"},{"level":3,"text":"Additional Documentation","anchor":"additional-documentation","htmlText":"Additional Documentation"},{"level":2,"text":"Contributing","anchor":"contributing","htmlText":"Contributing"},{"level":2,"text":"Reporting problems, asking questions","anchor":"reporting-problems-asking-questions","htmlText":"Reporting problems, asking questions"},{"level":2,"text":"For more information","anchor":"for-more-information","htmlText":"For more 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href="#triton-inference-server"><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://opensource.org/licenses/BSD-3-Clause" rel="nofollow"><img src="https://camo.githubusercontent.com/f7da0c60c3c35540f74d75a8003ca2f306dd5d9db99a534a5ec3e1e6b80150c6/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f4c6963656e73652d425344332d6c69676874677265792e737667" alt="License" data-canonical-src="https://img.shields.io/badge/License-BSD3-lightgrey.svg" style="max-width: 100%;"></a></p> <div class="markdown-alert markdown-alert-warning" dir="auto"><p class="markdown-alert-title" dir="auto"><svg class="octicon octicon-alert mr-2" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="M6.457 1.047c.659-1.234 2.427-1.234 3.086 0l6.082 11.378A1.75 1.75 0 0 1 14.082 15H1.918a1.75 1.75 0 0 1-1.543-2.575Zm1.763.707a.25.25 0 0 0-.44 0L1.698 13.132a.25.25 0 0 0 .22.368h12.164a.25.25 0 0 0 .22-.368Zm.53 3.996v2.5a.75.75 0 0 1-1.5 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>Warning</p><p dir="auto">You are currently on the <code>main</code> branch which tracks under-development progress towards the next release. The current release is version <a href="https://github.com/triton-inference-server/server/releases/latest">2.52.0</a> and corresponds to the 24.11 container release on NVIDIA GPU Cloud (NGC).</p> </div> <p dir="auto">Triton Inference Server is an open source inference serving software that streamlines AI inferencing. Triton enables teams to deploy any AI model from multiple deep learning and machine learning frameworks, including TensorRT, TensorFlow, PyTorch, ONNX, OpenVINO, Python, RAPIDS FIL, and more. Triton Inference Server supports inference across cloud, data center, edge and embedded devices on NVIDIA GPUs, x86 and ARM CPU, or AWS Inferentia. Triton Inference Server delivers optimized performance for many query types, including real time, batched, ensembles and audio/video streaming. Triton inference Server is part of <a href="https://www.nvidia.com/en-us/data-center/products/ai-enterprise/" rel="nofollow">NVIDIA AI Enterprise</a>, a software platform that accelerates the data science pipeline and streamlines the development and deployment of production AI.</p> <p dir="auto">Major features include:</p> <ul dir="auto"> <li><a href="https://github.com/triton-inference-server/backend#where-can-i-find-all-the-backends-that-are-available-for-triton">Supports multiple deep learning frameworks</a></li> <li><a href="https://github.com/triton-inference-server/fil_backend">Supports multiple machine learning frameworks</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#concurrent-model-execution">Concurrent model execution</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#dynamic-batcher">Dynamic batching</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#sequence-batcher">Sequence batching</a> and <a href="/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#implicit-state-management">implicit state management</a> for stateful models</li> <li>Provides <a href="https://github.com/triton-inference-server/backend">Backend API</a> that allows adding custom backends and pre/post processing operations</li> <li>Supports writing custom backends in python, a.k.a. <a href="https://github.com/triton-inference-server/backend/blob/main/docs/python_based_backends.md#python-based-backends">Python-based backends.</a></li> <li>Model pipelines using <a href="/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#ensemble-models">Ensembling</a> or <a href="https://github.com/triton-inference-server/python_backend#business-logic-scripting">Business Logic Scripting (BLS)</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/customization_guide/inference_protocols.md">HTTP/REST and GRPC inference protocols</a> based on the community developed <a href="https://github.com/kserve/kserve/tree/master/docs/predict-api/v2">KServe protocol</a></li> <li>A <a href="/triton-inference-server/server/blob/main/docs/customization_guide/inference_protocols.md#in-process-triton-server-api">C API</a> and <a href="/triton-inference-server/server/blob/main/docs/customization_guide/inference_protocols.md#java-bindings-for-in-process-triton-server-api">Java API</a> allow Triton to link directly into your application for edge and other in-process use cases</li> <li><a href="/triton-inference-server/server/blob/main/docs/user_guide/metrics.md">Metrics</a> indicating GPU utilization, server throughput, server latency, and more</li> </ul> <p dir="auto"><strong>New to Triton Inference Server?</strong> Make use of <a href="https://github.com/triton-inference-server/tutorials">these tutorials</a> to begin your Triton journey!</p> <p dir="auto">Join the <a href="https://www.nvidia.com/en-us/deep-learning-ai/triton-tensorrt-newsletter/" rel="nofollow">Triton and TensorRT community</a> and stay current on the latest product updates, bug fixes, content, best practices, and more. Need enterprise support? NVIDIA global support is available for Triton Inference Server with the <a href="https://www.nvidia.com/en-us/data-center/products/ai-enterprise/" rel="nofollow">NVIDIA AI Enterprise software suite</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Serve a Model in 3 Easy Steps</h2><a id="user-content-serve-a-model-in-3-easy-steps" class="anchor" aria-label="Permalink: Serve a Model in 3 Easy Steps" href="#serve-a-model-in-3-easy-steps"><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="# Step 1: Create the example model repository git clone -b r24.11 https://github.com/triton-inference-server/server.git cd server/docs/examples ./fetch_models.sh # Step 2: Launch triton from the NGC Triton container docker run --gpus=1 --rm --net=host -v ${PWD}/model_repository:/models nvcr.io/nvidia/tritonserver:24.11-py3 tritonserver --model-repository=/models # Step 3: Sending an Inference Request # In a separate console, launch the image_client example from the NGC Triton SDK container docker run -it --rm --net=host nvcr.io/nvidia/tritonserver:24.11-py3-sdk /workspace/install/bin/image_client -m densenet_onnx -c 3 -s INCEPTION /workspace/images/mug.jpg # Inference should return the following Image '/workspace/images/mug.jpg': 15.346230 (504) = COFFEE MUG 13.224326 (968) = CUP 10.422965 (505) = COFFEEPOT"><pre><span class="pl-c"><span class="pl-c">#</span> Step 1: Create the example model repository</span> git clone -b r24.11 https://github.com/triton-inference-server/server.git <span class="pl-c1">cd</span> server/docs/examples ./fetch_models.sh <span class="pl-c"><span class="pl-c">#</span> Step 2: Launch triton from the NGC Triton container</span> docker run --gpus=1 --rm --net=host -v <span class="pl-smi">${PWD}</span>/model_repository:/models nvcr.io/nvidia/tritonserver:24.11-py3 tritonserver --model-repository=/models <span class="pl-c"><span class="pl-c">#</span> Step 3: Sending an Inference Request</span> <span class="pl-c"><span class="pl-c">#</span> In a separate console, launch the image_client example from the NGC Triton SDK container</span> docker run -it --rm --net=host nvcr.io/nvidia/tritonserver:24.11-py3-sdk /workspace/install/bin/image_client -m densenet_onnx -c 3 -s INCEPTION /workspace/images/mug.jpg <span class="pl-c"><span class="pl-c">#</span> Inference should return the following</span> Image <span class="pl-s"><span class="pl-pds">'</span>/workspace/images/mug.jpg<span class="pl-pds">'</span></span>: 15.346230 (504) = COFFEE MUG 13.224326 (968) = CUP 10.422965 (505) = COFFEEPOT</pre></div> <p dir="auto">Please read the <a href="/triton-inference-server/server/blob/main/docs/getting_started/quickstart.md">QuickStart</a> guide for additional information regarding this example. The quickstart guide also contains an example of how to launch Triton on <a href="/triton-inference-server/server/blob/main/docs/getting_started/quickstart.md#run-on-cpu-only-system">CPU-only systems</a>. New to Triton and wondering where to get started? Watch the <a href="https://youtu.be/NQDtfSi5QF4" rel="nofollow">Getting Started video</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Examples and Tutorials</h2><a id="user-content-examples-and-tutorials" class="anchor" aria-label="Permalink: Examples and Tutorials" href="#examples-and-tutorials"><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">Check out <a href="https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/trial/" rel="nofollow">NVIDIA LaunchPad</a> for free access to a set of hands-on labs with Triton Inference Server hosted on NVIDIA infrastructure.</p> <p dir="auto">Specific end-to-end examples for popular models, such as ResNet, BERT, and DLRM are located in the <a href="https://github.com/NVIDIA/DeepLearningExamples">NVIDIA Deep Learning Examples</a> page on GitHub. The <a href="https://developer.nvidia.com/nvidia-triton-inference-server" rel="nofollow">NVIDIA Developer Zone</a> contains additional documentation, presentations, and examples.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Documentation</h2><a id="user-content-documentation" class="anchor" aria-label="Permalink: Documentation" href="#documentation"><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">Build and Deploy</h3><a id="user-content-build-and-deploy" class="anchor" aria-label="Permalink: Build and Deploy" href="#build-and-deploy"><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">The recommended way to build and use Triton Inference Server is with Docker images.</p> <ul dir="auto"> <li><a href="/triton-inference-server/server/blob/main/docs/customization_guide/build.md#building-with-docker">Install Triton Inference Server with Docker containers</a> (<em>Recommended</em>)</li> <li><a href="/triton-inference-server/server/blob/main/docs/customization_guide/build.md#building-without-docker">Install Triton Inference Server without Docker containers</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/customization_guide/compose.md">Build a custom Triton Inference Server Docker container</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/customization_guide/build.md#building-on-unsupported-platforms">Build Triton Inference Server from source</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/customization_guide/build.md#building-for-windows-10">Build Triton Inference Server for Windows 10</a></li> <li>Examples for deploying Triton Inference Server with Kubernetes and Helm on <a href="/triton-inference-server/server/blob/main/deploy/gcp/README.md">GCP</a>, <a href="/triton-inference-server/server/blob/main/deploy/aws/README.md">AWS</a>, and <a href="/triton-inference-server/server/blob/main/deploy/fleetcommand/README.md">NVIDIA FleetCommand</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/customization_guide/deploy.md">Secure Deployment Considerations</a></li> </ul> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Using Triton</h3><a id="user-content-using-triton" class="anchor" aria-label="Permalink: Using Triton" href="#using-triton"><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"><h4 tabindex="-1" class="heading-element" dir="auto">Preparing Models for Triton Inference Server</h4><a id="user-content-preparing-models-for-triton-inference-server" class="anchor" aria-label="Permalink: Preparing Models for Triton Inference Server" href="#preparing-models-for-triton-inference-server"><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">The first step in using Triton to serve your models is to place one or more models into a <a href="/triton-inference-server/server/blob/main/docs/user_guide/model_repository.md">model repository</a>. Depending on the type of the model and on what Triton capabilities you want to enable for the model, you may need to create a <a href="/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md">model configuration</a> for the model.</p> <ul dir="auto"> <li><a href="/triton-inference-server/server/blob/main/docs/user_guide/custom_operations.md">Add custom operations to Triton if needed by your model</a></li> <li>Enable model pipelining with <a href="/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#ensemble-models">Model Ensemble</a> and <a href="https://github.com/triton-inference-server/python_backend#business-logic-scripting">Business Logic Scripting (BLS)</a></li> <li>Optimize your models setting <a href="/triton-inference-server/server/blob/main/docs/user_guide/architecture.md#models-and-schedulers">scheduling and batching</a> parameters and <a href="/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#instance-groups">model instances</a>.</li> <li>Use the <a href="https://github.com/triton-inference-server/model_analyzer">Model Analyzer tool</a> to help optimize your model configuration with profiling</li> <li>Learn how to <a href="/triton-inference-server/server/blob/main/docs/user_guide/model_management.md">explicitly manage what models are available by loading and unloading models</a></li> </ul> <div class="markdown-heading" dir="auto"><h4 tabindex="-1" class="heading-element" dir="auto">Configure and Use Triton Inference Server</h4><a id="user-content-configure-and-use-triton-inference-server" class="anchor" aria-label="Permalink: Configure and Use Triton Inference Server" href="#configure-and-use-triton-inference-server"><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>Read the <a href="/triton-inference-server/server/blob/main/docs/getting_started/quickstart.md">Quick Start Guide</a> to run Triton Inference Server on both GPU and CPU</li> <li>Triton supports multiple execution engines, called <a href="https://github.com/triton-inference-server/backend#where-can-i-find-all-the-backends-that-are-available-for-triton">backends</a>, including <a href="https://github.com/triton-inference-server/tensorrt_backend">TensorRT</a>, <a href="https://github.com/triton-inference-server/tensorflow_backend">TensorFlow</a>, <a href="https://github.com/triton-inference-server/pytorch_backend">PyTorch</a>, <a href="https://github.com/triton-inference-server/onnxruntime_backend">ONNX</a>, <a href="https://github.com/triton-inference-server/openvino_backend">OpenVINO</a>, <a href="https://github.com/triton-inference-server/python_backend">Python</a>, and more</li> <li>Not all the above backends are supported on every platform supported by Triton. Look at the <a href="https://github.com/triton-inference-server/backend/blob/main/docs/backend_platform_support_matrix.md">Backend-Platform Support Matrix</a> to learn which backends are supported on your target platform.</li> <li>Learn how to <a href="/triton-inference-server/server/blob/main/docs/user_guide/optimization.md">optimize performance</a> using the <a href="https://github.com/triton-inference-server/perf_analyzer/blob/main/README.md">Performance Analyzer</a> and <a href="https://github.com/triton-inference-server/model_analyzer">Model Analyzer</a></li> <li>Learn how to <a href="/triton-inference-server/server/blob/main/docs/user_guide/model_management.md">manage loading and unloading models</a> in Triton</li> <li>Send requests directly to Triton with the <a href="/triton-inference-server/server/blob/main/docs/customization_guide/inference_protocols.md#httprest-and-grpc-protocols">HTTP/REST JSON-based or gRPC protocols</a></li> </ul> <div class="markdown-heading" dir="auto"><h4 tabindex="-1" class="heading-element" dir="auto">Client Support and Examples</h4><a id="user-content-client-support-and-examples" class="anchor" aria-label="Permalink: Client Support and Examples" href="#client-support-and-examples"><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 Triton <em>client</em> application sends inference and other requests to Triton. The <a href="https://github.com/triton-inference-server/client">Python and C++ client libraries</a> provide APIs to simplify this communication.</p> <ul dir="auto"> <li>Review client examples for <a href="https://github.com/triton-inference-server/client/blob/main/src/c%2B%2B/examples">C++</a>, <a href="https://github.com/triton-inference-server/client/blob/main/src/python/examples">Python</a>, and <a href="https://github.com/triton-inference-server/client/blob/main/src/java/src/main/java/triton/client/examples">Java</a></li> <li>Configure <a href="https://github.com/triton-inference-server/client#http-options">HTTP</a> and <a href="https://github.com/triton-inference-server/client#grpc-options">gRPC</a> client options</li> <li>Send input data (e.g. a jpeg image) directly to Triton in the <a href="https://github.com/triton-inference-server/server/blob/main/docs/protocol/extension_binary_data.md#raw-binary-request">body of an HTTP request without any additional metadata</a></li> </ul> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Extend Triton</h3><a id="user-content-extend-triton" class="anchor" aria-label="Permalink: Extend Triton" href="#extend-triton"><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="/triton-inference-server/server/blob/main/docs/user_guide/architecture.md">Triton Inference Server's architecture</a> is specifically designed for modularity and flexibility</p> <ul dir="auto"> <li><a href="/triton-inference-server/server/blob/main/docs/customization_guide/compose.md">Customize Triton Inference Server container</a> for your use case</li> <li><a href="https://github.com/triton-inference-server/backend">Create custom backends</a> in either <a href="https://github.com/triton-inference-server/backend/blob/main/README.md#triton-backend-api">C/C++</a> or <a href="https://github.com/triton-inference-server/python_backend">Python</a></li> <li>Create <a href="/triton-inference-server/server/blob/main/docs/user_guide/decoupled_models.md">decoupled backends and models</a> that can send multiple responses for a request or not send any responses for a request</li> <li>Use a <a href="/triton-inference-server/server/blob/main/docs/customization_guide/repository_agents.md">Triton repository agent</a> to add functionality that operates when a model is loaded and unloaded, such as authentication, decryption, or conversion</li> <li>Deploy Triton on <a href="/triton-inference-server/server/blob/main/docs/user_guide/jetson.md">Jetson and JetPack</a></li> <li><a href="https://github.com/triton-inference-server/python_backend/tree/main/inferentia">Use Triton on AWS Inferentia</a></li> </ul> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Additional Documentation</h3><a id="user-content-additional-documentation" class="anchor" aria-label="Permalink: Additional Documentation" href="#additional-documentation"><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><a href="/triton-inference-server/server/blob/main/docs/user_guide/faq.md">FAQ</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/README.md#user-guide">User Guide</a></li> <li><a href="/triton-inference-server/server/blob/main/docs/README.md#customization-guide">Customization Guide</a></li> <li><a href="https://docs.nvidia.com/deeplearning/triton-inference-server/release-notes/index.html" rel="nofollow">Release Notes</a></li> <li><a href="https://docs.nvidia.com/deeplearning/dgx/support-matrix/index.html" rel="nofollow">GPU, Driver, and CUDA Support Matrix</a></li> </ul> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Contributing</h2><a id="user-content-contributing" class="anchor" aria-label="Permalink: Contributing" href="#contributing"><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">Contributions to Triton Inference Server are more than welcome. To contribute please review the <a href="/triton-inference-server/server/blob/main/CONTRIBUTING.md">contribution guidelines</a>. If you have a backend, client, example or similar contribution that is not modifying the core of Triton, then you should file a PR in the <a href="https://github.com/triton-inference-server/contrib">contrib repo</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Reporting problems, asking questions</h2><a id="user-content-reporting-problems-asking-questions" class="anchor" aria-label="Permalink: Reporting problems, asking questions" href="#reporting-problems-asking-questions"><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 appreciate any feedback, questions or bug reporting regarding this project. When posting <a href="https://github.com/triton-inference-server/server/issues">issues in GitHub</a>, follow the process outlined in the <a href="https://stackoverflow.com/help/mcve" rel="nofollow">Stack Overflow document</a>. Ensure posted examples are:</p> <ul dir="auto"> <li>minimal – use as little code as possible that still produces the same problem</li> <li>complete – provide all parts needed to reproduce the problem. Check if you can strip external dependencies and still show the problem. The less time we spend on reproducing problems the more time we have to fix it</li> <li>verifiable – test the code you're about to provide to make sure it reproduces the problem. Remove all other problems that are not related to your request/question.</li> </ul> <p dir="auto">For issues, please use the provided bug report and feature request templates.</p> <p dir="auto">For questions, we recommend posting in our community <a href="https://github.com/triton-inference-server/server/discussions">GitHub Discussions.</a></p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">For more information</h2><a id="user-content-for-more-information" class="anchor" aria-label="Permalink: For more information" href="#for-more-information"><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">Please refer to the <a href="https://developer.nvidia.com/nvidia-triton-inference-server" rel="nofollow">NVIDIA Developer Triton page</a> for more information.</p> </article></div></div></div></div></div> <!-- --> <!-- --> <script type="application/json" id="__PRIMER_DATA_:R0:__">{"resolvedServerColorMode":"day"}</script></div> </react-partial> <input type="hidden" data-csrf="true" value="qgmLFQhtw43ou04ACNgLPfL9QZE+GFG0XXBwVIhnZNz1HOARvc4s3fJd9le1FHiXaKOB80Tcsk/0ZU4Fmo8Fqg==" /> </div> <div data-view-component="true" class="Layout-sidebar"> <div class="BorderGrid about-margin" data-pjax> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <div class="hide-sm hide-md"> <h2 class="mb-3 h4">About</h2> <p class="f4 my-3"> The Triton Inference Server provides an optimized cloud and edge inferencing solution. </p> <div class="my-3 d-flex flex-items-center"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link flex-shrink-0 mr-2"> <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> <span class="flex-auto min-width-0 css-truncate css-truncate-target width-fit"> <a 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8.477c.285.135.718.273 1.305.273s1.02-.138 1.305-.273L13 6.327Zm-10 0c.285.135.718.273 1.305.273s1.02-.138 1.305-.273L3 6.327Z"></path> </svg> Security policy </a> </div> <include-fragment src="/triton-inference-server/server/hovercards/citation/sidebar_partial?tree_name=main"> </include-fragment> <div class="mt-2"> <a href="/triton-inference-server/server/activity" data-view-component="true" class="Link Link--muted"> <svg text="gray" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-pulse mr-2"> <path d="M6 2c.306 0 .582.187.696.471L10 10.731l1.304-3.26A.751.751 0 0 1 12 7h3.25a.75.75 0 0 1 0 1.5h-2.742l-1.812 4.528a.751.751 0 0 1-1.392 0L6 4.77 4.696 8.03A.75.75 0 0 1 4 8.5H.75a.75.75 0 0 1 0-1.5h2.742l1.812-4.529A.751.751 0 0 1 6 2Z"></path> </svg> <span class="color-fg-muted">Activity</span> </a> </div> <div class="mt-2"> <a href="/triton-inference-server/server/custom-properties" data-view-component="true" class="Link Link--muted"> <svg text="gray" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-note mr-2"> <path d="M0 3.75C0 2.784.784 2 1.75 2h12.5c.966 0 1.75.784 1.75 1.75v8.5A1.75 1.75 0 0 1 14.25 14H1.75A1.75 1.75 0 0 1 0 12.25Zm1.75-.25a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h12.5a.25.25 0 0 0 .25-.25v-8.5a.25.25 0 0 0-.25-.25ZM3.5 6.25a.75.75 0 0 1 .75-.75h7a.75.75 0 0 1 0 1.5h-7a.75.75 0 0 1-.75-.75Zm.75 2.25h4a.75.75 0 0 1 0 1.5h-4a.75.75 0 0 1 0-1.5Z"></path> </svg> <span class="color-fg-muted">Custom properties</span> </a> </div> <h3 class="sr-only">Stars</h3> <div class="mt-2"> <a href="/triton-inference-server/server/stargazers" data-view-component="true" class="Link Link--muted"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-star mr-2"> <path d="M8 .25a.75.75 0 0 1 .673.418l1.882 3.815 4.21.612a.75.75 0 0 1 .416 1.279l-3.046 2.97.719 4.192a.751.751 0 0 1-1.088.791L8 12.347l-3.766 1.98a.75.75 0 0 1-1.088-.79l.72-4.194L.818 6.374a.75.75 0 0 1 .416-1.28l4.21-.611L7.327.668A.75.75 0 0 1 8 .25Zm0 2.445L6.615 5.5a.75.75 0 0 1-.564.41l-3.097.45 2.24 2.184a.75.75 0 0 1 .216.664l-.528 3.084 2.769-1.456a.75.75 0 0 1 .698 0l2.77 1.456-.53-3.084a.75.75 0 0 1 .216-.664l2.24-2.183-3.096-.45a.75.75 0 0 1-.564-.41L8 2.694Z"></path> </svg> <strong>8.4k</strong> stars </a> </div> <h3 class="sr-only">Watchers</h3> <div class="mt-2"> <a href="/triton-inference-server/server/watchers" data-view-component="true" class="Link Link--muted"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-eye mr-2"> <path d="M8 2c1.981 0 3.671.992 4.933 2.078 1.27 1.091 2.187 2.345 2.637 3.023a1.62 1.62 0 0 1 0 1.798c-.45.678-1.367 1.932-2.637 3.023C11.67 13.008 9.981 14 8 14c-1.981 0-3.671-.992-4.933-2.078C1.797 10.83.88 9.576.43 8.898a1.62 1.62 0 0 1 0-1.798c.45-.677 1.367-1.931 2.637-3.022C4.33 2.992 6.019 2 8 2ZM1.679 7.932a.12.12 0 0 0 0 .136c.411.622 1.241 1.75 2.366 2.717C5.176 11.758 6.527 12.5 8 12.5c1.473 0 2.825-.742 3.955-1.715 1.124-.967 1.954-2.096 2.366-2.717a.12.12 0 0 0 0-.136c-.412-.621-1.242-1.75-2.366-2.717C10.824 4.242 9.473 3.5 8 3.5c-1.473 0-2.825.742-3.955 1.715-1.124.967-1.954 2.096-2.366 2.717ZM8 10a2 2 0 1 1-.001-3.999A2 2 0 0 1 8 10Z"></path> </svg> <strong>146</strong> watching </a> </div> <h3 class="sr-only">Forks</h3> <div class="mt-2"> <a href="/triton-inference-server/server/forks" data-view-component="true" class="Link Link--muted"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo-forked mr-2"> <path d="M5 5.372v.878c0 .414.336.75.75.75h4.5a.75.75 0 0 0 .75-.75v-.878a2.25 2.25 0 1 1 1.5 0v.878a2.25 2.25 0 0 1-2.25 2.25h-1.5v2.128a2.251 2.251 0 1 1-1.5 0V8.5h-1.5A2.25 2.25 0 0 1 3.5 6.25v-.878a2.25 2.25 0 1 1 1.5 0ZM5 3.25a.75.75 0 1 0-1.5 0 .75.75 0 0 0 1.5 0Zm6.75.75a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5Zm-3 8.75a.75.75 0 1 0-1.5 0 .75.75 0 0 0 1.5 0Z"></path> </svg> <strong>1.5k</strong> forks </a> </div> <div class="mt-2"> <a class="Link--muted" href="/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2Ftriton-inference-server%2Fserver&report=triton-inference-server+%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="/triton-inference-server/server/releases" data-view-component="true" class="Link--primary no-underline Link"> Releases <span title="73" data-view-component="true" class="Counter">73</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="/triton-inference-server/server/releases/tag/v2.52.0"> <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;">Release 2.52.0 corresponding to NGC container 24.11</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="2024-11-26T23:13:19Z" class="no-wrap">Nov 26, 2024</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="/triton-inference-server/server/releases" data-view-component="true" class="Link"> + 72 releases </a></div> </div> </div> <div class="BorderGrid-row" hidden> <div class="BorderGrid-cell"> <include-fragment src="/triton-inference-server/server/used_by_list" accept="text/fragment+html"> </include-fragment> </div> </div> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <h2 class="h4 mb-3"> <a href="/triton-inference-server/server/graphs/contributors" data-view-component="true" class="Link--primary no-underline Link d-flex flex-items-center"> Contributors <span title="129" data-view-component="true" class="Counter ml-1">129</span> </a></h2> <ul class="list-style-none d-flex flex-wrap mb-n2"> <li class="mb-2 mr-2" > <a 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class="color-fg-default text-bold mr-1">Python</span> <span>54.2%</span> </a> </li> <li class="d-inline"> <a class="d-inline-flex flex-items-center flex-nowrap Link--secondary no-underline text-small mr-3" href="/triton-inference-server/server/search?l=shell" data-ga-click="Repository, language stats search click, location:repo overview"> <svg style="color:#89e051;" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-dot-fill mr-2"> <path d="M8 4a4 4 0 1 1 0 8 4 4 0 0 1 0-8Z"></path> </svg> <span class="color-fg-default text-bold mr-1">Shell</span> <span>23.3%</span> </a> </li> <li class="d-inline"> <a class="d-inline-flex flex-items-center flex-nowrap Link--secondary no-underline text-small mr-3" href="/triton-inference-server/server/search?l=c%2B%2B" data-ga-click="Repository, language stats search click, location:repo overview"> <svg style="color:#f34b7d;" aria-hidden="true" height="16" viewBox="0 0 16 16" 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