Discover the best Ml open source repositories on GitHub. Explore trending tools, live star counts, source code, and developer projects updated daily.
Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device.
The open-source AI workbench for scientific research
Fast, small, and fully autonomous AI personal assistant infrastructure, any OS, any platform — deploy anywhere, swap anything 🦀
An Open Source Machine Learning Framework for Everyone
Open-source inference server and production cluster for all the models your agent needs.
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Train Large Language Models on MLX.
Visualizer for neural network, deep learning and machine learning models
Zero-cloud AI memory that works everywhere. SQLite-backed. One pure-Python dependency.
Speaker diarization in Rust with pyannote-level accuracy. 1790–5970x realtime on NVIDIA GPUs, 430–910x on Apple Silicon.
Apple MLX native implementations of state-of-the-art generative image & video models
High-performance neural networks engine for web, built on top of TypeGPU
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Open standard for machine learning interoperability
Machine learning powered Karaoke app (with scores!)
SwarmUI (formerly StableSwarmUI), A Modular Stable Diffusion Web-User-Interface, with an emphasis on making powertools easily accessible, high performance, and extensibility.
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
Platform for Machine Learning projects on Software Engineering
Keep Python on your laptop. Run PyTorch operations and hold tensors on a remote GPU, including from a Mac with no CUDA installation.
Scalable and Performant Data Loading