Showing 101-120 of 366 projects
Improved Denoising Diffusion Probabilistic Models for AI applications
ClaraVerse is a privacy-first, local AI workspace with a Local LLM chat, Stable Diffusion, and automation tools.
An open-source library for quantizing diffusion models to 4-bit precision, absorbing outliers through low-rank components.
A browser-based implementation of the Stable Diffusion AI model, enabling in-browser image generation.
GLIDE is a diffusion-based text-conditional image synthesis model that allows developers to generate images from text descriptions.
MAGI-1 is a powerful autoregressive model for generating high-quality video at scale, built for vibe coders who work with AI tools.
Open-source imitation learning algorithms for mobile robotics and AI-powered applications.
A Python library that enables editing of images using AI-powered tools like Segment Anything, ControlNet, and Stable Diffusion.
A Python tool for the Stable Diffusion WebUI that allows for the visualization of model differences.
A curated list of Generative AI tools, works, models, and references for developers
Efficient vision foundation models for high-resolution generation and perception.
This repository provides a Chinese localization extension for the stable-diffusion-webui, an AI image generation tool.
An implementation of Dreambooth for Stable Diffusion, with a focus on training faces, objects, and styles.
Self Forcing: Bridging Training and Inference in Autoregressive Video Diffusion
A Python library for efficient video generative modeling using pyramidal flow matching techniques.
An open-source video generation ecosystem built on top of diffusion models for AI-powered video synthesis.
A unified inference and post-training framework for accelerated video generation powered by AI.
A comprehensive collection of research papers on automatic speech recognition, speech synthesis, and related topics.
A collection of prompt patterns and strategies for designing AI-powered applications and tools.
A Python tool that uses GPT-4, FFmpeg, and OpenCV to automatically analyze videos, extract the most interesting sections, and crop them for an improved viewing experience.
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