🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
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A high-throughput and memory-efficient inference and serving engine for LLMs
🧑🏫 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, ... 🧠
SGLang is a high-performance serving framework for large language models and multimodal models.
Training-free language model modification: Remove censorship, suppress slop, reduce sycophancy, and more
SOTA Open Source TTS
OpenMMLab Detection Toolbox and Benchmark
Faster Whisper transcription with CTranslate2
pix2tex: Using a ViT to convert images of equations into LaTeX code.
Nano vLLM
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.
A framework for few-shot evaluation of language models.
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
Translate manga/image 一键翻译各类图片内文字 https://cotrans.touhou.ai/ (no longer working)
Scalable and user friendly neural :brain: forecasting algorithms.
allRank is a framework for training learning-to-rank neural models based on PyTorch.
零基础入门大模型（LLM）的基础教程：从零手写 GPT-2，一行行看懂大模型是怎么工作的 | Build GPT-2 from scratch in PyTorch, step by step
Plan and train German transformer models.