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??? 60+ Implementations/tutorials of deep learning papers with side-by-side notes ?; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ? reinforcement learning (ppo, dqn), capsnet, distillation, ... ?

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Port of OpenAI's Whisper model in C/C++

SOTA Open Source TTS

? A ranked list of awesome machine learning Python libraries. Updated weekly.

《李宏毅深度学习教程》（李宏毅老师推荐?，苹果书?），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

Natural Language Processing Tutorial for Deep Learning Researchers

pix2tex: Using a ViT to convert images of equations into LaTeX code.

SGLang is a fast serving framework for large language models and vision language models.

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.