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d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg> <span class="ml-4 pl-0.5 ">like</span></button> <button class="flex items-center border-l px-1.5 py-1 text-gray-400 hover:bg-gray-50 focus:bg-gray-100 focus:outline-none dark:hover:bg-gray-900 dark:focus:bg-gray-800" title="See users who liked this repository">0</button></div> </h1> <div class="mb-3 flex flex-wrap md:mb-4"><a class="mb-1 mr-1 md:mb-1.5 md:mr-1.5 rounded-lg" href="/models?pipeline_tag=reinforcement-learning"><div class="tag tag-white "><div class="tag-ico -ml-2 tag-ico-red"><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path fill="currentColor" d="M18 10h2v2h-2zm-6 0h2v2h-2z"></path><path fill="currentColor" d="M26 20h-5v-2h1a2.002 2.002 0 0 0 2-2v-4h2v-2h-2V8a2.002 2.002 0 0 0-2-2h-2V2h-2v4h-4V2h-2v4h-2a2.002 2.002 0 0 0-2 2v2H6v2h2v4a2.002 2.002 0 0 0 2 2h1v2H6a2.002 2.002 0 0 0-2 2v8h2v-8h20v8h2v-8a2.002 2.002 0 0 0-2-2ZM10 8h12v8H10Zm3 10h6v2h-6Z"></path></svg></div> <span>Reinforcement Learning</span> </div></a><a class="mb-1 mr-1 md:mb-1.5 md:mr-1.5 rounded-lg" href="/models?library=sample-factory"><div class="tag tag-white "> <span>sample-factory</span> </div></a><a class="mb-1 mr-1 md:mb-1.5 md:mr-1.5 rounded-lg" href="/models?library=tensorboard"><div class="tag tag-white "> <span>TensorBoard</span> </div></a><a class="mb-1 mr-1 md:mb-1.5 md:mr-1.5 rounded-lg" href="/models?other=deep-reinforcement-learning"><div class="tag tag-white "> <span>deep-reinforcement-learning</span> </div></a><a class="mb-1 mr-1 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