Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Transformers | 102,023 | 64 | 911 | 8 hours ago | 91 | June 21, 2022 | 728 | apache-2.0 | Python | |
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. | ||||||||||
Pytorch | 67,308 | 146 | 8 hours ago | 23 | August 10, 2022 | 12,029 | other | Python | ||
Tensors and Dynamic neural networks in Python with strong GPU acceleration | ||||||||||
Yolov5 | 38,906 | 9 hours ago | 35 | May 21, 2022 | 349 | agpl-3.0 | Python | |||
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite | ||||||||||
Made With Ml | 33,193 | a month ago | 5 | May 15, 2019 | 11 | mit | Jupyter Notebook | |||
Learn how to responsibly develop, deploy and maintain production machine learning applications. | ||||||||||
Ray | 25,778 | 80 | 199 | 11 hours ago | 76 | June 09, 2022 | 2,850 | apache-2.0 | Python | |
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads. | ||||||||||
Deepspeed | 25,149 | 12 | 10 hours ago | 53 | May 25, 2022 | 868 | apache-2.0 | Python | ||
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. | ||||||||||
Fastai | 23,942 | 184 | 117 | 3 days ago | 143 | July 04, 2022 | 156 | apache-2.0 | Jupyter Notebook | |
The fastai deep learning library | ||||||||||
Lightning | 23,427 | 7 | 389 | 12 hours ago | 221 | June 01, 2022 | 685 | apache-2.0 | Python | |
Deep learning framework to train, deploy, and ship AI products Lightning fast. | ||||||||||
Netron | 22,953 | 4 | 63 | a day ago | 489 | July 04, 2022 | 26 | mit | JavaScript | |
Visualizer for neural network, deep learning, and machine learning models | ||||||||||
Annotated_deep_learning_paper_implementations | 22,464 | 1 | 18 days ago | 76 | June 27, 2022 | 17 | mit | Jupyter Notebook | ||
🧑🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠 |
这是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门。
由于本人水平有限,在写此教程的时候参考了一些网上的资料,在这里对他们表示敬意,我会在每个引用中附上原文地址,方便大家参考。
深度学习的技术在飞速的发展,同时PyTorch也在不断更新,且本人会逐步完善相关内容。
由于PyTorch版本更迭,教程的版本会与PyTorch版本,保持一致。
pytorch大版本更新的主要变动总结 当前版本 1.11
国内的镜像,速度很快,不会被墙:https://www.pytorch.wiki/
PDF文件目前还没有找到好的生成方法,有熟悉这方面的朋友可以联系我,感激不尽
群号:760443051
点击链接加入群聊【PyTorch Handbook 交流6群】:https://jq.qq.com/?_wv=1027&k=X4Ro6uWv
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不要再加了
公众账号每日分享干货文章
修改错别字请直接提issue或PR
PR时请注意版本
有问题也请直接提issue
感谢
神经网络简介 注:本章在本地使用微软的Edge打开会崩溃,请使Chrome Firefox打开查看
在PyTorch中使用DistributedDataParallel进行多GPU分布式模型训练
transforms的常用操作总结
pytorch的损失函数总结
pytorch的优化器总结
script目录是我写的将ipynb转换成在线的版本和pdf文件的脚本,因为还在测试阶段,所以有什么问题请大家提出