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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

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

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.

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

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

🔍 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