Machine Learning Engineering Open Book

A straightforward method for training your LLM, from downloading data to generating text.

⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc.

🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools

OneTrainer is a one-stop solution for all your Diffusion training needs.

PyTorch native quantization and sparsity for training and inference

Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.

Avalanche: an End-to-End Library for Continual Learning based on PyTorch.

Distribute and run AI workloads on Kubernetes magically in Python, like PyTorch for ML infra.

Train speculative decoding models effortlessly and port them smoothly to SGLang serving.

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools, with 10x faster training through evolutionary hyperparameter optimization.

Train Tesseract LSTM with make

[NeurIPS 2025 D&B Spotlight] Scaling Data for SWE-agents

A unified end-to-end machine intelligence platform

Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.

Fault tolerance for PyTorch (HSDP, LocalSGD, DiLoCo, Streaming DiLoCo)

Guideline following Large Language Model for Information Extraction

Autonomous AI research swarm — runs ~100 overnight LLM training experiments unattended. Fork of karpathy/autoresearch with Digital Cognitive Labor routing.

🗂 Split folders with files (i.e. images) into training, validation and test (dataset) folders

A visual-based graph node editor for training computer vision models.