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<!DOCTYPE NETSCAPE-Bookmark-file-1>
<!-- This is an automatically generated file.
It will be read and overwritten.
DO NOT EDIT! -->
<META HTTP-EQUIV="Content-Type" CONTENT="text/html; charset=UTF-8">
<TITLE>Bookmarks</TITLE>
<H1>Bookmarks</H1>
<DL><p>
<DT><H3 ADD_DATE="1673511251" LAST_MODIFIED="1681379495" PERSONAL_TOOLBAR_FOLDER="true">书签栏</H3>
<DL><p>
<DT><A HREF="http://10.31.37.82/zentao/user-login-L3plbnRhby8=.html" ADD_DATE="1675824952" ICON="data:image/png;base64,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">用户登录 - 禅道</A>
<DT><A HREF="https://www.oschina.net/p/emsite" ADD_DATE="1677662875" ICON="data:image/png;base64,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">分布式全自动快速开发框架平台 </A>
<DT><A HREF="https://www.sitelike.org/similar/holyubofficial.net/" ADD_DATE="1680749119" ICON="data:image/png;base64,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">Top 12 Similar websites like holyubofficial.net and alternatives</A>
<DT><A HREF="https://towardsdatascience.com/build-your-own-grammarly-in-python-6fb4297c189c" ADD_DATE="1681276660"></A>
<DT><A HREF="https://github.com/Torantulino/Auto-GPT" ADD_DATE="1681278929" ICON="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABeklEQVQ4jY3Tv2qVQRAF8PPdP7k3itoE7SOIKFZiDAZsfBJFfBDRQjBFGkFiJ/gKerGwsRAsvaKFFhYWgo3GxEA0P4vMhTUk4sDy7c6cMztzZr9kn2EFD/Eem7Xele/yfnxLnMP9Isxst9bMfhRmriX2MMLE/9ukOL1ZktUKvMANvMIGpnhT+9e4jmeFvTcjL2ELv7BevjFOYYgBFjBfsbXCbuLiIMnNJPPV0Tb6XddtJ9luJPqKDv0kO0n6SY4kuZVSeBc/cabRpWt06mZnLJaYu5im+oPPGB06pr9Fn1aCjV6SYcWOJhm3Nx9A7pKMkywk6ZIMe0k+JJHkRJLlruugf0ALg67rJFlJcrI4H4NHVc53fMLZf1RwDm/xu9peD5brcBuPa/8cSw3xAp7gW8V3apSXZoC1quI87uApTjcJFptXuFXf1VbVPl7WSK+1txdmjC9Nkom9f6fXggZ40ICON7Fj1feOvWc/zGGGK9XGqPGNcBdX9+P/AO1cPr7g2LjWAAAAAElFTkSuQmCC">GitHub - Torantulino/Auto-GPT: An experimental open-source attempt to make GPT-4 fully autonomous.</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/79064602" ADD_DATE="1681351570" ICON="data:image/png;base64,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">LSTM细节分析理解（pytorch版） - 知乎</A>
<DT><A HREF="https://blog.csdn.net/weixin_45727931/article/details/114369073" ADD_DATE="1681362980" ICON="data:image/png;base64,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">Pytorch循环神经网络（RNN）快速入门与实战_pytorch rnn_Hello3q3q的博客-CSDN博客</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/352276786" ADD_DATE="1681364425" ICON="data:image/png;base64,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">pytorch中如何做seq2seq - 知乎</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/575573336" ADD_DATE="1681369234" ICON="data:image/png;base64,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">[NeurIPS 2022] VideoMAE: 简单高效的视频自监督预训练新范式 - 知乎</A>
<DT><A HREF="https://blog.csdn.net/flyingluohaipeng/article/details/126648783" ADD_DATE="1681369347" ICON="data:image/png;base64,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">论文解读 X-CLIP : Expanding Language-Image Pretrained Models for General Video Recognition_cv_lhp的博客-CSDN博客</A>
<DT><A HREF="https://pytorch.org/docs/stable/dynamo/index.html" ADD_DATE="1681379317" ICON="data:image/png;base64,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">TorchDynamo Overview — PyTorch 2.0 documentation</A>
<DT><H3 ADD_DATE="1681379495" LAST_MODIFIED="1681379495">AGI Computer Control</H3>
<DL><p>
<DT><A HREF="https://www.kaggle.com/code/jessysisca/agi-computer-control/edit" ADD_DATE="1681379495" ICON="data:image/png;base64,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">agi_computer_control | Kaggle</A>
<DT><H3 ADD_DATE="1681379495" LAST_MODIFIED="1681379495">ViT models</H3>
<DL><p>
<DT><A HREF="https://pytorch.org/docs/stable/dynamo/installation.html" ADD_DATE="1681379495" ICON="data:image/png;base64,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">Installing TorchDynamo — PyTorch 2.0 documentation</A>
<DT><A HREF="https://discuss.pytorch.org/t/grad-is-none-when-doing-loss-backward/84661/3" ADD_DATE="1681379495" ICON="data:image/png;base64,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">Grad is None when doing loss.backward - autograd - PyTorch Forums</A>
<DT><A HREF="https://neptune.ai/blog/pytorch-loss-functions" ADD_DATE="1681379495" ICON="data:image/png;base64,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">PyTorch Loss Functions: The Ultimate Guide - neptune.ai</A>
<DT><A HREF="https://discuss.huggingface.co/t/finetuning-gpt2-with-user-defined-loss/163/13" ADD_DATE="1681379495" ICON="data:image/png;base64,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">Finetuning GPT2 with user defined loss - Beginners - Hugging Face Forums</A>
<DT><A HREF="https://huggingface.co/docs/transformers/training" ADD_DATE="1681379495" ICON="data:image/png;base64,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">Fine-tune a pretrained model</A>
<DT><A HREF="https://github.com/leoxiaobin/deep-high-resolution-net.pytorch/issues/38" ADD_DATE="1681379495">github.com</A>
<DT><A HREF="https://pytorch.org/docs/stable/generated/torch.nn.MSELoss.html#:~:text=The%20unreduced%20%28i.e.%20with%20reduction%20set%20to%20%27none%27%29,If%20reduction%20is%20not%20%27none%27%20%28default%20%27mean%27%29%2C%20then%3A" ADD_DATE="1681379495" ICON="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAACaUlEQVQ4jXVTPU8UURQ9982bHWAWhGUj4UPEuAEZiGJYC43FiuFLrVQoRBOjhYWVv0AojaV/gViIhWhcIkaksTEx0Si4LiRABIKRrwDrMsvMuxbMkAHX29zk5t7z7rnnPCBP9AMCAJbb6quXOhqOAQB7tYMhDxYYIALUYqI+WlRsvGDH6QcwQ4DKByDyDPP8xerycIkxoguKu8xTUzEYK51WEwPEAP0XgACeO19bVlJU9sqUIr5pu30lyVS64oR1o9jUv823N8YI4CAdEXx9JlFXGokcGg6H5NnVbbsvkpx4CgCu4rGs496a3vk+8+Xc8cP/0PHX2rzSNMTXWnj5snUTAJ4BWrBv5VJTl321ZW6po7HZnxMMaATwarfVHS4IXV/NbvdHX08OMiB7AddXgAGNnZ1ZoVR5oUGPghQYAHQhbmdzzrr9a+Oxd0wncBs1BCA6mk5lcu4TQ2hdP9tqqglg4fORGppB/Lnq0+If8kCD0bN7PNJBHwxBFDbCsf0qEBEpcg8O+jHgZYdcBkDSc5DwXaeUSrvgU2xZoXyue5iAIIAVRGtOsVrPqGkAEJanwI6DQbNARteP4h4BigHtfQKSe3YzjcNZS9SVmrq4n2P19shYesG71a4c4wlo8eLm0ZAUF7Lbdk/pyI/nwQ1mOxsrIyFtqFCKuG3nzoSTqa/7AAjg3+0NVYVF+ktTl60Z233nKh4mUltE4rQkuqMJ0jM5p7csOTnsz+z52i8snawwzdroA10Td5lRRwQo5i2ARrK2O1D+ZnKCgT319n0MHwQAJiyEIpWxmJJ6Aa9tzNV8XFjxekTQyn8B1iL28idBXqcAAAAASUVORK5CYII=">MSELoss — PyTorch 2.0 documentation</A>
<DT><A HREF="https://www.educba.com/pytorch-mseloss/" ADD_DATE="1681379495" ICON="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAC+ElEQVQ4jW1TTWyUZRB+5v3Z/XbZ7aZUSqULrd1S2i3SpAKJCRCjCerJ9GAiKYjhIvEnhljjAQ9NBMIB8KJJ49+hB03sxcR4IyEx6EExFGM32MpSWouFtrtll939/t53PLirbXVOk8wzT2bmeQaoBwNUTym/65k9M93PZ9bW1tTXBTUABPBib+/jTInzluKHQ3ZqIUe+Da36YNf01z/WcYIAu46g0Xy/Z/tBRzsTSZXcuhjKvOVYZItOpRcCGRhExjzwhf7cxNzGCQQBvDyQbldOZDwhaWvRPBx3dfBE1ff6l70HFyWqpk3Smw7LqzM9w68xRsU6AgCgeOSd5oTqLJKdqCSrJ5vgn07FywPbbn43EoTeoRVT/EaRuz2hxUfTvfnPf0i/GPtnheWn0+3KRK/pkJrcqr+v5fpcrpjN3CYh08zY2zw1fQMA8v3PvR9H/F2XHe2a8EDvb199z4AQUsueqIM2T9mfW67P5RjQrKiowYrdmgGAP7ODrzhcGYoJT1su31GhN1dXgBVrxKIC7LGdB4DZTsiUhoCBNVofXunbOZJU9rhhgxXz8DKMGOm+dWW+obBSMlj1pCIo0QwAnbMIV7cBykDEIC9uYoGSqeZrjPOf5iY/GwUsA3SzfWgzJUy7gC1Pe5IXRIT2Lz3b8SgAw5q+CDX8QNqlItsLJVk91DY1+ckoYK8BmgDelKi+JY2/GQBQOtI5xi/v5MILj50FAGbQ0sHuwXv7dnQ1rj2VzUYa+R99e08tZA9cnUF3FABQOJLeUxnuKvsvZdzCUNfJ/7Ns3YmR1b7M6fLuAb7bNzi0zomF4Y7Xm6T6MPQYrocvydJ4WKJfdbVW84VqpVA+KQPxaork/oJvLrXkfn+73vvvLxSOdrwRgzzjCJkyFYuKy0Xrs0s+bUmRUqWKReDxe4/8cusc12WkNeP9TXIss1sxn+CAnoJHOxCSRigWjWuvhJVgrPWn2cn/fONGEgCYP5WOJe4lW0nH1Uq0eTnz8eUHGzEA8BemsVWqL0RqowAAAABJRU5ErkJggg==">PyTorch MSELoss() | What is PyTorch MSELoss() | How to use?</A>
<DT><A HREF="https://pytorch.org/docs/stable/generated/torch.nn.MSELoss.html" ADD_DATE="1681379495" ICON="data:image/png;base64,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">MSELoss — PyTorch 2.0 documentation</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/87870736" ADD_DATE="1681379495" ICON="data:image/png;base64,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">python中np.reshape，np.transpose和axis - 知乎</A>
<DT><A HREF="https://numpy.org/doc/stable/reference/generated/numpy.rollaxis.html" ADD_DATE="1681379495" ICON="data:image/png;base64,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">numpy.rollaxis — NumPy v1.24 Manual</A>
<DT><A HREF="https://blog.csdn.net/SL_World/article/details/114149076" ADD_DATE="1681379495" ICON="data:image/png;base64,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">PIL Image与tensor在PyTorch图像预处理时的转换_img should be tensor image. got <class 'pil.image._SL_World的博客-CSDN博客</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/575573336" ADD_DATE="1681379495" ICON="data:image/png;base64,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">[NeurIPS 2022] VideoMAE: 简单高效的视频自监督预训练新范式 - 知乎</A>
<DT><A HREF="https://github.com/MCG-NJU/VideoMAE" ADD_DATE="1681379495" ICON="data:image/png;base64,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">GitHub - MCG-NJU/VideoMAE: [NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training</A>
<DT><A HREF="https://pytorch.org/docs/stable/generated/torch.nn.functional.mse_loss.html" ADD_DATE="1681379495" ICON="data:image/png;base64,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">torch.nn.functional.mse_loss — PyTorch 2.0 documentation</A>
<DT><A HREF="https://blog.csdn.net/zfhsfdhdfajhsr/article/details/115637954" ADD_DATE="1681379495" ICON="data:image/png;base64,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">【Pytorch基础】torch.nn.MSELoss损失函数_一穷二白到年薪百万的博客-CSDN博客</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/445009191" ADD_DATE="1681379495" ICON="data:image/png;base64,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">理解Pytorch的loss.backward()和optimizer.step() - 知乎</A>
<DT><A HREF="https://blog.csdn.net/yangwangnndd/article/details/95622893" ADD_DATE="1681379495" ICON="data:image/png;base64,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">torch之optimizer.step() 和loss.backward()和scheduler.step()的关系与区别_Nicola-Zhang的博客-CSDN博客</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/435669796" ADD_DATE="1681379495" ICON="data:image/png;base64,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">pytorch优化器与学习率设置详解 - 知乎</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/445009191" ADD_DATE="1681379495" ICON="data:image/png;base64,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">理解Pytorch的loss.backward()和optimizer.step() - 知乎</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/352276786" ADD_DATE="1681379495" ICON="data:image/png;base64,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">pytorch中如何做seq2seq - 知乎</A>
<DT><A HREF="https://blog.csdn.net/qq_38153833/article/details/88060268" ADD_DATE="1681379495" ICON="data:image/png;base64,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">cv2和PIL.Image之间的转换_pil image 转为cv2_绑个蝴蝶结的博客-CSDN博客</A>
<DT><A HREF="https://blog.csdn.net/qq_42079689/article/details/102537600" ADD_DATE="1681379495" ICON="data:image/png;base64,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">Opencv-python（cv2）改变图像尺寸的cv2.resize（）函数_风雪夜归人o的博客-CSDN博客</A>
<DT><A HREF="https://jdhao.github.io/2017/11/06/resize-image-to-square-with-padding/#:~:text=The%20full%20code%20to%20resize%20and%20pad%20an,old_size%5D%29%20%23%20new_size%20should%20be%20in%20%28width%2C%20" ADD_DATE="1681379495" ICON="data:image/png;base64,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">How to Resize, Pad Image to Square Shape and Keep Its Aspect Ratio in Python - jdhao's digital space</A>
<DT><A HREF="https://github.com/Meituan-AutoML/CPVT" ADD_DATE="1681379495" ICON="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABeklEQVQ4jY3Tv2qVQRAF8PPdP7k3itoE7SOIKFZiDAZsfBJFfBDRQjBFGkFiJ/gKerGwsRAsvaKFFhYWgo3GxEA0P4vMhTUk4sDy7c6cMztzZr9kn2EFD/Eem7Xele/yfnxLnMP9Isxst9bMfhRmriX2MMLE/9ukOL1ZktUKvMANvMIGpnhT+9e4jmeFvTcjL2ELv7BevjFOYYgBFjBfsbXCbuLiIMnNJPPV0Tb6XddtJ9luJPqKDv0kO0n6SY4kuZVSeBc/cabRpWt06mZnLJaYu5im+oPPGB06pr9Fn1aCjV6SYcWOJhm3Nx9A7pKMkywk6ZIMe0k+JJHkRJLlruugf0ALg67rJFlJcrI4H4NHVc53fMLZf1RwDm/xu9peD5brcBuPa/8cSw3xAp7gW8V3apSXZoC1quI87uApTjcJFptXuFXf1VbVPl7WSK+1txdmjC9Nkom9f6fXggZ40ICON7Fj1feOvWc/zGGGK9XGqPGNcBdX9+P/AO1cPr7g2LjWAAAAAElFTkSuQmCC">GitHub - Meituan-AutoML/CPVT</A>
<DT><A HREF="https://github.com/Meituan-AutoML/Twins" ADD_DATE="1681379495" ICON="data:image/png;base64,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">GitHub - Meituan-AutoML/Twins: Two simple and effective designs of vision transformer, which is on par with the Swin transformer</A>
<DT><A HREF="https://github.com/Meituan-AutoML/Twins/blob/main/logs/pcpvt_s.txt" ADD_DATE="1681379495" ICON="data:image/png;base64,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">Twins/pcpvt_s.txt at main · Meituan-AutoML/Twins · GitHub</A>
<DT><A HREF="https://github.com/BlinkDL/RWKV-LM" ADD_DATE="1681379495" ICON="data:image/png;base64,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">GitHub - BlinkDL/RWKV-LM: RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.</A>
<DT><A HREF="https://johanwind.github.io/2023/03/23/rwkv_details.html" ADD_DATE="1681379495" ICON="data:image/png;base64,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">How the RWKV language model works | The Good Minima</A>
<DT><A HREF="https://pypi.org/project/rwkvstic/" ADD_DATE="1681379495" ICON="data:image/png;base64,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">rwkvstic · PyPI</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/79064602" ADD_DATE="1681379495" ICON="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAACcklEQVQ4jT3TTahVdRQF8N8+59yr5numZlmgQVQUUaOkkUKDoonRQIIgCMLyQYOa5CxMigZBDjIsIiyKjIqmFk0alDxq0CTpSUEiWYZUfqX3Xt85578bnFeDDXuyF2utvVbYn2PFS8aeFtbXI/oKFWqhQb0ylTQSav8Ib/vZC42pV8x5XidV9DNcI2MkhMxOBJCIaGVJ8+btdbsS9uZljTUqqVbvukd+cZLJFGNpLMT/jGikBqtQudzora1CKRPVw9vkwYfY+TFlAxrxyyW2rmf1eJDQhzhzlb+uSo35RqcgdPLRu0RTc/Qxevx6niMn2L+ds1OudOLODeL14/LFYzTrqKITZcrNm8WOW9j1AUtnefUbHjzEyXP8ORXbj7DjXb48JTeOhVZET5UdCssz7jvAsUVKEWcuMPmDi5PBwOmM9gpXe5kpdWQnGzkATGbs3sEN93PbJrmwTdy7SV7AtGWULKesioiCjuhFE5XMZbFlHXdfT92wcQ2/XVDmGtEWSiF6tEKuPLRFJ6tMjFg6ze435MKHXJzx/nfiucPy6BJrR3TLw0FfBsY6sheVHFBHYzTsfYDzE3loF089IrqW1Q2lZUSsbVYYdERHI2SEaK9w041i306eeE+c+pvPFsSTH8lrV/H9s6Ivcut6XlscjM2WJggtW67j02f4/DiffEu28uBXnPidO17m8OPywNf8cIZZhTFdq4rYkxezmNu8gVs3icWfpEpEkP2wq1doVysRbhRjhFmVvbesVp09JxZ/lOoh+2nwRAymRUU16E9FpVbrvNm4ZJ9KrbGnasyV8l/vkEMjFZFl0KwWKudNvOO0ff8CDNsVBiQlEB0AAAAASUVORK5CYII=">LSTM细节分析理解（pytorch版） - 知乎</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/404107277" ADD_DATE="1681379495" ICON="data:image/png;base64,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">视觉神经网络模型优秀开源工作：timm 库使用方法和代码解读 - 知乎</A>
<DT><A HREF="https://pypi.org/project/timm/" ADD_DATE="1681379495" ICON="data:image/png;base64,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">timm · PyPI</A>
<DT><A HREF="https://blog.csdn.net/weixin_44966641/article/details/119299678" ADD_DATE="1681379495" ICON="data:image/png;base64,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">Positional Encodings in ViTs 近期各视觉Transformer中的位置编码方法总结及代码解析 1_vit位置编码_Adenialzz的博客-CSDN博客</A>
<DT><A HREF="https://blog.csdn.net/weixin_44966641/article/details/118730730?spm=1001.2014.3001.5501" ADD_DATE="1681379495" ICON="data:image/png;base64,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">PyTorch中的torch.nn.Parameter() 详解_Adenialzz的博客-CSDN博客</A>
<DT><A HREF="https://github.com/lucidrains/vit-pytorch" ADD_DATE="1681379495" ICON="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABeklEQVQ4jY3Tv2qVQRAF8PPdP7k3itoE7SOIKFZiDAZsfBJFfBDRQjBFGkFiJ/gKerGwsRAsvaKFFhYWgo3GxEA0P4vMhTUk4sDy7c6cMztzZr9kn2EFD/Eem7Xele/yfnxLnMP9Isxst9bMfhRmriX2MMLE/9ukOL1ZktUKvMANvMIGpnhT+9e4jmeFvTcjL2ELv7BevjFOYYgBFjBfsbXCbuLiIMnNJPPV0Tb6XddtJ9luJPqKDv0kO0n6SY4kuZVSeBc/cabRpWt06mZnLJaYu5im+oPPGB06pr9Fn1aCjV6SYcWOJhm3Nx9A7pKMkywk6ZIMe0k+JJHkRJLlruugf0ALg67rJFlJcrI4H4NHVc53fMLZf1RwDm/xu9peD5brcBuPa/8cSw3xAp7gW8V3apSXZoC1quI87uApTjcJFptXuFXf1VbVPl7WSK+1txdmjC9Nkom9f6fXggZ40ICON7Fj1feOvWc/zGGGK9XGqPGNcBdX9+P/AO1cPr7g2LjWAAAAAElFTkSuQmCC">GitHub - lucidrains/vit-pytorch: Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/599150009" ADD_DATE="1681379495" ICON="data:image/png;base64,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">RWKV：用RNN达到Transformer性能，且支持并行模式和长程记忆，既快又省显存，已在14B参数规模检验 - 知乎</A>
<DT><A HREF="https://cn.bing.com/search?q=pytorch+view&qs=n&form=QBRE&sp=-1&lq=0&pq=pytorch+view&sc=10-12&sk=&cvid=8B0A649D4BB044DA901D883BDD3D4AD2&ghsh=0&ghacc=0&ghpl=" ADD_DATE="1681379495" ICON="data:image/png;base64,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">pytorch view - 搜索</A>
<DT><A HREF="https://blog.csdn.net/york1996/article/details/81949843" ADD_DATE="1681379495" ICON="data:image/png;base64,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">PyTorch中view的用法_pytorch view_York1996的博客-CSDN博客</A>
<DT><A HREF="https://blog.csdn.net/weixin_45727931/article/details/114369073" ADD_DATE="1681379495" ICON="data:image/png;base64,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">Pytorch循环神经网络（RNN）快速入门与实战_pytorch rnn_Hello3q3q的博客-CSDN博客</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/617864689" ADD_DATE="1681379495" ICON="data:image/png;base64,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">多模态大语言模型OpenFlamingo开源了 - 知乎</A>
<DT><A HREF="https://github.com/mlfoundations/open_flamingo#initializing-an-openflamingo-model" ADD_DATE="1681379495" ICON="data:image/png;base64,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">GitHub - mlfoundations/open_flamingo: An open-source framework for training large multimodal models.</A>
<DT><A HREF="https://blog.csdn.net/zqx951102/article/details/121707077" ADD_DATE="1681379495" ICON="data:image/png;base64,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">VIT中特殊class token的一些问题_zqx951102的博客-CSDN博客</A>
<DT><A HREF="https://zhuanlan.zhihu.com/p/385406085" ADD_DATE="1681379495" ICON="data:image/png;base64,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">一文带你掌（放）握（弃）ViT(Vision Transformer)（原理解读+实践代码） - 知乎</A>
<DT><A HREF="https://github.com/pytorch/torchdynamo" ADD_DATE="1681379495" ICON="data:image/png;base64,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">GitHub - pytorch/torchdynamo: A Python-level JIT compiler designed to make unmodified PyTorch programs faster.</A>
<DT><A HREF="https://blog.csdn.net/weixin_61445075/article/details/124543483" ADD_DATE="1681379495" ICON="data:image/png;base64,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">np.newaxis,tensor.squeeze(),np.hstack,torch.hstack,torch.cat,tensor.reshape的使用_tensor.cat_LUQC638的博客-CSDN博客</A>
<DT><A HREF="https://blog.csdn.net/flyingluohaipeng/article/details/126648783" ADD_DATE="1681379495" ICON="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAIAAACQkWg2AAAB/klEQVQ4jU2SPWtUYRCFz5n3bvbubhISoyJiJxEsEkglghZJZUTUJkhAUoja2WihgohFQPAXaGVhk8rGRkQrURDEFOL3B2idkDXJ7t3Nve8ci7ubZOozZ2aeMyzmptAvSSBpBgkxgkQIkOQOkgCAZLeaJEi1NkBDWgeEzXUkFVZTuIPcaSjVkqPb5bEZTp/H4aPMc//0Hs+X9Psb0hrlILm9kuRw5+XbNjsPuX//yNEx239Inbbfu6IvH5jWISU9fzNlmV26FWbn/d0rf7SI5oosaPosF25gZC9iLH1ZzE0JRLeN8YnwYEl/fsSb8+xkTOvyiK0O9h3ERhMSAZAGgKTy3E6eppmePcHmOhtDgmjG2iDXVtjnAcAAyCNrDYxPSNLXZVZTxYIlZTmSBKSkciUrb0BSwfAe5DnW11DmUE7u6bhN3/opRHTbSALSGgSaARDAEOCuYmu72QAwJGq39OszLXDqhP6tKjrc6VEbTdUaHDugIufODRAt6OVTxcIWrtuZi6imCokGUkwet7sPbfExBqpy72Etc0C7xVMX7OodVCroZGquojHIoRECvvzG71+DnLRdSQPIWhiftJlzODLJ4VF1Mvz9qeXXevsCRcEQ+hN2Ps/UaaPIUWswJJKjm6EoWB8syZLsPV8PgiLTGlhHjIoFSaR10OQRpSPwH79sFlWOAVADAAAAAElFTkSuQmCC">论文解读 X-CLIP : Expanding Language-Image Pretrained Models for General Video Recognition_cv_lhp的博客-CSDN博客</A>
<DT><A HREF="https://github.com/openai/consistency_models" ADD_DATE="1681379495" ICON="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABeklEQVQ4jY3Tv2qVQRAF8PPdP7k3itoE7SOIKFZiDAZsfBJFfBDRQjBFGkFiJ/gKerGwsRAsvaKFFhYWgo3GxEA0P4vMhTUk4sDy7c6cMztzZr9kn2EFD/Eem7Xele/yfnxLnMP9Isxst9bMfhRmriX2MMLE/9ukOL1ZktUKvMANvMIGpnhT+9e4jmeFvTcjL2ELv7BevjFOYYgBFjBfsbXCbuLiIMnNJPPV0Tb6XddtJ9luJPqKDv0kO0n6SY4kuZVSeBc/cabRpWt06mZnLJaYu5im+oPPGB06pr9Fn1aCjV6SYcWOJhm3Nx9A7pKMkywk6ZIMe0k+JJHkRJLlruugf0ALg67rJFlJcrI4H4NHVc53fMLZf1RwDm/xu9peD5brcBuPa/8cSw3xAp7gW8V3apSXZoC1quI87uApTjcJFptXuFXf1VbVPl7WSK+1txdmjC9Nkom9f6fXggZ40ICON7Fj1feOvWc/zGGGK9XGqPGNcBdX9+P/AO1cPr7g2LjWAAAAAElFTkSuQmCC">GitHub - openai/consistency_models: Official repo for consistency models.</A>
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