Awesome Opensource Ai

An Open Source Machine Learning Framework for Everyone

🤗 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.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Open Source Computer Vision Library

🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

12 Weeks, 24 Lessons, AI for All!

Deep Learning for humans

Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

Clone a voice in 5 seconds to generate arbitrary speech in real-time

Deepfakes Software For All

Learn it. Build it. Ship it for others.

We write your reusable computer vision tools. 💜

Learn how to develop, deploy and iterate on production-grade ML applications.

Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

Streamlit — A faster way to build and share data apps.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Making large AI models cheaper, faster and more accessible

Cross-platform, customizable ML solutions for live and streaming media.

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.

💫 Industrial-strength Natural Language Processing (NLP) in Python

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

Label Studio is a multi-type data labeling and annotation tool with standardized output format

The fastai deep learning library

A game theoretic approach to explain the output of any machine learning model.

Faster Whisper transcription with CTranslate2

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

Graph Neural Network Library for PyTorch

ncnn is a high-performance neural network inference framework optimized for the mobile platform

🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Open standard for machine learning interoperability

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

High-performance In-browser LLM Inference Engine

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org

Computer Vision Annotation Tool (CVAT) is a leading platform for building high-quality visual datasets for vision AI. It offers open-source, cloud, and enterprise products, as well as labeling services, for image, video, and 3D annotation with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.

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

Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.

Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.

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.

Open-source simulator for autonomous driving research.

An open source implementation of CLIP.

Open Machine Learning Compiler Framework

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

A Library for Advanced Deep Time Series Models for General Time Series Analysis.

A PyTorch-based Speech Toolkit

Low-code framework for building custom LLMs, neural networks, and other AI models