6 Repos
Tools for importing, organizing, and switching between different pre-trained diffusion model weights.
Distinct from Diffusion Models: Focuses on the management and switching of model files rather than the execution interface or training.
Explore 6 awesome GitHub repositories matching artificial intelligence & ml · Diffusion Model Managers. Refine with filters or upvote what's useful.
DiffusionBee is a Stable Diffusion desktop client for macOS that functions as an AI image generator and editor. It allows for the local generation of images from text prompts and the management of diffusion models without requiring external cloud services or technical setup. The application includes a local diffusion model manager for importing and switching between custom trained model files to achieve specific artistic styles. It also features a system for tracking generation history and uploading assets to a public gallery. The software covers several image synthesis and manipulation work
Provides a system for managing and switching between custom trained model files to achieve specific styles.
This project is a plugin for Krita that integrates Stable Diffusion image generation and editing tools directly into the painting interface. It functions as a remote diffusion backend client, bridging the digital canvas to local or remote servers to handle the computation required for AI image generation. The system distinguishes itself through a real-time painting interface that translates brushstrokes into generated imagery as the artist works. It acts as a structural orchestrator, using sketches, depth maps, and poses to maintain precise composition, and provides a generative inpainting to
Includes tools for importing, organizing, and switching between different pre-trained diffusion model checkpoints.
This project is an on-device AI SDK providing a framework for running large language models, vision models, and speech models locally. It serves as an orchestration layer for local LLM execution, ensuring data privacy and offline availability by utilizing hardware acceleration on the device. The SDK is distinguished by its comprehensive voice and multimodal capabilities, including a coordinated voice pipeline for activity detection, speech-to-text, and text-to-speech synthesis. It also provides a dedicated implementation kit for local retrieval-augmented generation and tools for processing co
Manages the registration and downloading of diffusion model packages for local image generation.
StabilityMatrix is a centralized installer and orchestrator for Stable Diffusion web interfaces and their dependencies. It functions as a generative AI workspace and portable runtime, providing a unified interface to install and update AI image generation packages within isolated environments to prevent global system conflicts. The project distinguishes itself through a shared model manager that imports, organizes, and shares checkpoints across different installations. It utilizes a central model repository and filesystem mapping to allow multiple packages to access the same large binary asse
Organizes and imports large libraries of diffusion model checkpoints from remote hubs into a shared directory.
SD.Next is an all-in-one web interface and multi-backend inference engine for generating, editing, and processing images and videos using diffusion models. It functions as a comprehensive tool for diffusion model management and an automated image processing pipeline for bulk operations. The project is distinguished by its hardware-backend abstraction layer, which provides automatic detection and acceleration for NVIDIA CUDA, AMD ROCm, Intel OpenVINO, and DirectML. It features a headless generative API and a programmatic command interface, allowing users to trigger tasks via REST API or CLI wi
Provides tools for downloading, quantizing, and optimizing diffusion model weights to reduce VRAM usage.
VoltaML-fast-stable-diffusion is a generative system designed for high-performance image synthesis from text prompts. It provides a comprehensive environment for executing inference tasks, managing pre-trained machine learning models, and integrating visual asset creation into external applications and workflows. The project distinguishes itself through multi-modal interaction capabilities, including a browser-based web interface for direct generation and a messaging platform integration that allows users to trigger and monitor tasks via chat commands. It supports automated creative workflows
Provides utilities for searching, downloading, and organizing pre-trained machine learning models for custom generation workflows.