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swesmith

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

torchao

PyTorch native quantization and sparsity for training and inference

optimum

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

sagemaker-training

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

torchft-nightly

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

swanlab

⚡️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.

dstack

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

split-folders

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

kubetorch

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

runhouse

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

tokenicer

A (nicer) tokenizer you want to use for model inference and training: with all known peventable gotchas normalized or auto-fixed.

datasetrising

Toolchain for creating custom datasets and training Stable Diffusion (1.x, 2.x, XL) models and LoRAs

tensorbored-nightly

TensorBored: Fixing TensorBoard's deficiencies

pytorch-accelerated

A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required. Docs: https://pytorch-accelerated.readthedocs.io/en/latest/

avalanche-lib

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

deepepochs

Pytorch模型训练工具

lightseq

LightSeq: A High Performance Library for Sequence Processing and Generation

awex

A high-performance RL training-inference weight synchronization framework, designed to enable second-level parameter updates from training to inference in RL workflows

neptune-sklearn

Experiment tracking for scikit-learn. 🧩 Log, organize, visualize and compare model metrics, parameters, dataset versions, and more.

mlx-lm-lora

Train LLMs on Apple silicon with MLX and the Hugging Face Hub

torchtraining-nightly

Functional & flexible neural network training with PyTorch.

mlpug

MLPug is a library for training and evaluating Machine Learning (ML) models, able to use different ML libraries as backends

neptune-tensorflow-keras

💡 Experiment tracking for TensorFlow/Keras. Log, organize, and compare model metrics, learning curves, hyperparameters, dataset versions, and more.

easymodels

Easily find and view pre-trained AI models and deep learning projects through the command line :computer: