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🤗 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.

A high-throughput and memory-efficient inference and serving engine for LLMs

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

SGLang is a high-performance serving framework for large language models and multimodal models.

SOTA Open Source TTS

Fully automatic censorship removal for language models

Faster Whisper transcription with CTranslate2

🏆 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

MNN: A blazing-fast, lightweight inference engine battle-tested by Alibaba, powering high-performance on-device LLMs and Edge AI.

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.

🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.

Code for the paper "Jukebox: A Generative Model for Music"

A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.

🔍 An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)

Quantization, kernels, runtime and inference engine for mobiles, wearables, smart home and robots.

A programmable Mixture-of-Models router for heterogeneous LLM inference

An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

不玩晦涩不搞少数派的 AI 入门圣经，从学生到工程师都能轻松掌握。涵盖神经网络到大模型、顶层设计到微观原理、工程实现到算法基础。 学完后，大家能彻底看懂为什么下一 token 预测这个看似不起眼的能力可以改变世界，也能发现原来 AI 并没有想象中那么神秘、那么高不可攀。 Let's just beat it !

【三年面试五年模拟】AIGC/LLM/AI Agent算法工程师面试资源平台。涵盖AIGC、LLM大模型、AI Agent、具身智能、传统深度学习、计算机视觉、自然语言处理、自动驾驶、机器学习、强化学习、大数据挖掘、世界模型、元宇宙、AGI等AI行业面试笔试干货经验与核心跨周期知识。

Scalable and user friendly neural :brain: forecasting algorithms.

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

Foundation Architecture for (M)LLMs

Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)

PyTorch native quantization for training and inference

Community maintained hardware plugin for vLLM on Ascend