4 Repos
Processes for teaching Stable Diffusion to recognize specific entities or styles using small, specialized datasets.
Distinct from Stable Diffusion Ecosystem: Candidates are broad ecosystem lists or inference engines; this focuses specifically on the training process for custom subjects.
Explore 4 awesome GitHub repositories matching artificial intelligence & ml · Custom Stable Diffusion Training. Refine with filters or upvote what's useful.
This project is a Dreambooth implementation designed to personalize Stable Diffusion models. It serves as an AI image personalization tool and model tuner that enables the creation of unique subject identifiers to generate consistent, personalized images. The system focuses on subject-driven image synthesis by fine-tuning pre-trained diffusion models on small, custom datasets. This allows the model to recognize specific people, objects, or artistic styles and place those learned subjects into diverse contexts via text-to-image conditioning. The implementation includes a diffusion model optim
Allows users to teach Stable Diffusion to recognize specific people, objects, or artistic styles using small image sets.
sd-scripts is a suite of utilities designed for fine-tuning generative models, preprocessing datasets, and converting model weights. It provides a collection of scripts for executing Stable Diffusion training through methods such as DreamBooth, textual inversion, and full fine-tuning, alongside a framework for creating and managing Low-Rank Adaptation weights. The project features specialized capabilities for model weight conversion between different architectures and precision formats. It includes tools for merging adaptation weights into base models, extracting weights from trained models,
Ships a comprehensive collection of scripts for fine-tuning Stable Diffusion models using various methods and optimizations.
lora-scripts ist ein Fine-Tuning-Toolkit, das für die Anpassung von Basis-Diffusionsmodellen an spezifische Stile oder Motive entwickelt wurde. Es bietet eine spezialisierte Reihe von Skripten und Tools zur Ausführung von Low-Rank-Adaptation- und Dreambooth-Trainingsjobs. Das Projekt verfügt über eine webbasierte grafische Oberfläche, die den Trainings-Workflow verwaltet und es Benutzern ermöglicht, Jobs ohne manuelle Skriptbearbeitung zu konfigurieren und auszuführen. Diese Oberfläche bildet Benutzereingaben auf Hyperparameter ab und bietet ein Echtzeit-Dashboard zur Überwachung von Trainingsmetriken und Verlustkurven, um die Modellkonvergenz zu verfolgen. Das System enthält einen Dataset-Tagging-Manager zum Organisieren und Bearbeiten von Bild-Labels. Um eine konsistente Ausführung über verschiedene Hardware-Hosts hinweg zu gewährleisten, wird die Trainingsumgebung als vorkonfiguriertes, containerisiertes Setup bereitgestellt.
Provides a complete workflow for training custom Stable Diffusion models to recognize specific entities or styles.
LoRA Easy Training Scripts is a desktop-based graphical interface designed to manage the end-to-end workflow of training custom machine learning models. The application serves as a centralized dashboard for preparing datasets, configuring neural network parameters, and orchestrating the execution of complex training jobs. The tool distinguishes itself by providing a visual environment that abstracts the command-line requirements of model fine-tuning. It enables users to manage training queues, allowing for the automated sequencing of multiple tasks to maximize hardware utilization. By maintai
Provides a graphical interface for configuring and executing Stable Diffusion LoRA training jobs.