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Hugging Face Accelerate launches and trains PyTorch models across devices and distributed configurations.

Enables single machine or distributed training and evaluation of deep learning models.

PEFT provides parameter-efficient fine-tuning methods for adapting pretrained machine learning models.

FEDOT automates machine learning model development through its modeling framework.

Archai supports neural architecture search with fast, reproducible, and modular research tools.

m2cgen converts machine learning models into native code for multiple programming languages without runtime dependencies.

LeRobot provides tools and learning resources for developing AI systems for robotics.

Octo provides a transformer-based policy for robots, with code to train and fine-tune it.

PyTorch Lightning helps pretrain and fine-tune AI models across one or many GPUs with minimal code changes.

Knet provides a deep learning framework developed at Koç University for building models.

PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.

Use Learnergy, a Python library for training and working with energy-based machine learning models.

This repository includes examples and a guide for fine-tuning Stable Diffusion models.

LightlyTrain supports pretraining, fine-tuning, and distillation for computer vision models.

P-tuning v2 is a deep prompt tuning strategy designed as an alternative to full model fine-tuning.

This repository implements DreamBooth subject fine-tuning for Stable Diffusion using textual inversion.

Detecto supports building and training computer vision models with the PyTorch machine learning framework.

ML_Forgex trains, evaluates, and predicts with machine learning models on cleaned datasets.

oumi supports fine-tuning, evaluation, and deployment of open-weight language models.

DeepSpeed optimizes distributed training and inference for deep learning models.

Deeplearning4j provides tools for training and deploying deep learning models in the JVM.

Determined manages distributed model training, hyperparameter tuning, experiment tracking, and resources.

OpenMetricLearning provides metric learning pipelines, models, and a model zoo.

This Common Lisp repository collects algorithms for online linear classification.