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Awesome-pytorch-list 翻译工作进行中......
| Date | Stars |
|---|---|
| 2026-07-24 | 1793 |
| 2026-07-25 | 1793 |
| 2026-07-28 | 1793 |
| 2026-07-30 | 1793 |
| 2026-08-06 | 1793 |
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Awesome-Pytorch-list｜厉害的Pytorch项目
========================
## [English Version](https://github.com/bharathgs/Awesome-pytorch-list)
## Contents｜内容
- [Awesome-Pytorch-list｜厉害的Pytorch项目](#awesome-pytorch-list%E5%8E%89%E5%AE%B3%E7%9A%84pytorch%E9%A1%B9%E7%9B%AE)
- [English Version](#english-version)
- [Contents｜内容](#contents%E5%86%85%E5%AE%B9)
- [Pytorch & related libraries｜Pytorch & 相关库](#pytorch--related-librariespytorch--%E7%9B%B8%E5%85%B3%E5%BA%93)
- [NLP & Speech Processing｜自然语言处理 & 语音处理](#nlp--speech-processing%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86--%E8%AF%AD%E9%9F%B3%E5%A4%84%E7%90%86)
- [CV｜计算机视觉](#cv%E8%AE%A1%E7%AE%97%E6%9C%BA%E8%A7%86%E8%A7%89)
- [Probabilistic/Generative Libraries｜概率库和生成库](#probabilisticgenerative-libraries%E6%A6%82%E7%8E%87%E5%BA%93%E5%92%8C%E7%94%9F%E6%88%90%E5%BA%93)
- [Other libraries｜其他库](#other-libraries%E5%85%B6%E4%BB%96%E5%BA%93)
- [Tutorials & books & examples｜教程 & 书籍 & 示例](#tutorials--books--examples%E6%95%99%E7%A8%8B--%E4%B9%A6%E7%B1%8D--%E7%A4%BA%E4%BE%8B)
- [Paper implementations｜论文实现](#paper-implementations%E8%AE%BA%E6%96%87%E5%AE%9E%E7%8E%B0)
- [Talks & conferences｜报告 & 会议](#talks--conferences%E6%8A%A5%E5%91%8A--%E4%BC%9A%E8%AE%AE)
- [Pytorch elsewhere ｜ Pytorch相关](#pytorch-elsewhere--pytorch%E7%9B%B8%E5%85%B3)
## Pytorch & related libraries｜Pytorch & 相关库
1. [pytorch](http://pytorch.org): Tensors and Dynamic neural networks in Python with strong GPU acceleration | 使用强GPU加速的Python张量计算和动态神经网络.
### NLP & Speech Processing｜自然语言处理 & 语音处理:
1. <kbd>2800+</kbd> [text](https://github.com/pytorch/text): 针对文本数据和NLP数据集的数据加载和抽象。
2. <kbd>1300+</kbd> [pytorch-seq2seq](https://github.com/IBM/pytorch-seq2seq): Pytorch中处理seq2seq的开源框架。
3. <kbd>1000-</kbd> [anuvada](https://github.com/Sandeep42/anuvada): NLP可解释模型。
4. <kbd>1300+</kbd> [audio](https://github.com/pytorch/audio): 简单的音频I/O。
5. <kbd>1000-</kbd> [loop](https://github.com/facebookresearch/loop): 一种跨多说话者的语音生成方法。
6. <kbd>null</kbd> [fairseq](https://github.com/facebookresearch/fairseq-py): Facebook开发的Sequence-to-Sequence python工具包。
7. <kbd>1000-</kbd> [speech](https://github.com/awni/speech): 语音转文字的端到端模型实现。
8. <kbd>5100+</kbd> [OpenNMT-py](https://github.com/OpenNMT/OpenNMT-py): 开源神经机器翻译 http://opennmt.net.
9. <kbd>2300+</kbd> [neuralcoref](https://github.com/huggingface/neuralcoref): 在spaCy中使用神经网络实现快速共指消解。
10. <kbd>1000+</kbd> [sentiment-discovery](https://github.com/NVIDIA/sentiment-discovery): 基于规模的无监督语言模型在稳健情绪分类中的应用。
11. <kbd>2800+</kbd> [MUSE](https://github.com/facebookresearch/MUSE): 一个多语言无监督或有监督词语嵌入库。
12. <kbd>1000-</kbd> [nmtpytorch](https://github.com/lium-lst/nmtpytorch): PyTorch中的Sequence-to-Sequence框架。
13. <kbd>1000-</kbd> [pytorch-wavenet](https://github.com/vincentherrmann/pytorch-wavenet): 快速生成WaveNet的实现。
14. <kbd>1000-</kbd> [Tacotron-pytorch](https://github.com/soobinseo/Tacotron-pytorch): Tacotron: 端到端语音合成。
15. <kbd>10300+</kbd> [AllenNLP](https://github.com/allenai/allennlp): 开源NLP研究库，基于PyTorch。[http://www.allennlp.org/](https://allennlp.org)
16. <kbd>1900+</kbd> [PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP): 为加速NLP研究设立的一个库，包含神经网络层、文本处理模块和众多数据集。 pytorchnlp.readthedocs.io
17. <kbd>1000-</kbd> [quick-nlp](https://github.com/outcastofmusic/quick-nlp): 基于FastAI的Pytorch NLP库。
18. <kbd>4900+</kbd> [TTS](https://github.com/mozilla/TTS): 文本转语音的深度学习框架。
19. <kbd>2800+</kbd> [LASER](https://github.com/facebookresearch/LASER): LASER是一个用来计算和使用多语言语句嵌入的库。
20. <kbd>1100+</kbd> [pyannote-audio](https://github.com/pyannote/pyannote-audio): 用于说话人分类的神经构建块：语音活动检测, 说话人变化检测, 说话人嵌入。
21. <kbd>1000-</kbd> [gensen](https://github.com/Maluuba/gensen): 基于大规模多任务学习的通用句子表示。
22. <kbd>1000-</kbd> [translate](https://github.com/pytorch/translate): 翻译——一个PyTorch语言库。
23. <kbd>3900+</kbd> [espnet](https://github.com/espnet/espnet): 端到端语音处理工具集。 espnet.github.io/espnet
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matched fp:39c5c76c7535df7a, topic:deep-learning, topic:neural-network, topic:pytorch