Open Source Machine Learning Projects
Discover 191 open source Machine Learning repositories from GitHub, each with an analysis of what it does, key features, use cases and alternatives. Machine Learning projects here are most often combined with Python, Deep Learning and LLM. Last updated October 4, 2026.
191 repositories · updated October 4, 2026
GPT-SoVITS: Clone Voices and Generate Speech from Text
GPT-SoVITS is a Python toolkit for voice cloning, speech conversion, and text-to-speech. It supports zero-shot synthesis from a short reference clip and fine-tuning with about one minute of voice data, with a WebUI for preparing data and training models.
GLM-4.5: Run Agentic Reasoning and Coding Models
GLM-4.5 is a family of open-weight mixture-of-experts models for reasoning, coding, and tool-using agents. It includes large and more compact variants, with deployment and fine-tuning guidance for teams with substantial GPU resources.
txtinstruct: Build Instruction-Tuned Models from Your Data
txtinstruct is a Python framework for creating instruction-following datasets and training instruction-tuned models. It is intended for people who want greater control over dataset licensing or to incorporate their own data.
riffusion-hobby: Generate Music Audio with Stable Diffusion
Riffusion-hobby is a Python library and application for generating music and audio with stable diffusion, including prompt interpolation and spectrogram-to-audio conversion. It suits developers and experimenters who want to run inference locally, but is no longer actively maintained.
deepface: Analyze and Recognize Faces in Python
DeepFace is a Python library that combines face recognition models and detection tools behind a simple API. Use it to verify identities, search face collections, generate embeddings, or estimate facial attributes.
audio2photoreal: Generate Photorealistic Avatars from Audio
A PyTorch research project for generating photorealistic human face and body motion from conversational audio. It includes person-specific pretrained models, training code, and access to the annotated dataset.
mlx-examples: Explore Machine Learning Models with MLX
A collection of standalone Python examples for the MLX machine learning framework, spanning language, image, video, audio, and multimodal models. Use it to learn MLX or adapt example implementations for experiments on supported hardware.
open-r1: Reproduce DeepSeek-R1 Training and Evaluation
Open R1 is Hugging Face’s toolkit and research project for reproducing the DeepSeek-R1 pipeline with open datasets, training scripts, and evaluation workflows. It is no longer maintained; its training work has moved to TRL.
llama-cpp-python: Run llama.cpp Models from Python
Python bindings for llama.cpp let developers run GGUF language models locally through a high-level API, low-level C bindings, or an OpenAI-compatible server. Useful when you want local inference and control over hardware backends.
FuncVul: Detect Vulnerabilities in Code Functions
FuncVul is a research model for detecting vulnerable code chunks within C/C++ and Python functions. It uses fine-tuned GraphCodeBERT and provides six labeled datasets for evaluating function-level vulnerability detection.
LlamaFactory: Fine-Tune Large Language and Vision Models
LlamaFactory provides CLI and web interfaces for fine-tuning a broad range of language and vision models. It supports parameter-efficient methods and preference training, with workflows for training, inference, and model export.
pytorch-deep-learning: Learn PyTorch Through Hands-On Lessons
A free, code-first PyTorch course for learning deep learning through notebooks, exercises, and projects. It guides beginners from tensor fundamentals to transfer learning, experiment tracking, and model deployment.