The Best examples/stable-diffusion-finetuning at main · LambdaLabsML/examples Alternatives in 2026

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

DreamBooth describes fine-tuning text-to-image diffusion models to generate images of specific subjects.

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

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.

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

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

This repository implements random forest models in Common Lisp for classification tasks.

This Common Lisp repository collects algorithms for online linear classification.

This metric-learn repository contains Python implementations of metric learning algorithms.

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

autoai automates regression and classification modeling in Python through model search and hyperparameter tuning.

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

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

Fine-tune LLaMA on consumer hardware with alpaca-lora and its LoRA training approach.

Katib automates machine learning on Kubernetes, including hyperparameter tuning and neural architecture search.

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

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

Learnergy is a Python library for energy-based machine learning models.

TensorFlow Model Optimization provides Keras and TensorFlow tools for model quantization and pruning.

doddle-model is an in-memory machine learning library for Scala, built on Breeze with a scikit-learn-like API using typeclasses.

AutoGluon provides tools for automated machine learning and model development.

FEDOT automates machine learning model development through its modeling framework.

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