A pipeline parallel training script for diffusion models.
Las características principales de tdrussell/diffusion-pipe son: Video Generation, Video Training Tools.
Las alternativas de código abierto para tdrussell/diffusion-pipe incluyen: huggingface/diffusers — Diffusers is a PyTorch-based library and generative AI framework used to build, train, and deploy diffusion pipelines… modelscope/diffsynth-studio — DiffSynth-Studio is a comprehensive platform for the lifecycle management of generative diffusion models, providing a… bghira/simpletuner — A general fine-tuning kit geared toward image/video/audio diffusion models. hao-ai-lab/fastvideo — FastVideo is a comprehensive system for accelerated video generation, serving as a video generation inference engine,… kohya-ss/musubi-tuner. shengshu-ai/minwm.
FastVideo is a comprehensive system for accelerated video generation, serving as a video generation inference engine, a video diffusion training framework, and a modular pipeline orchestrator. It provides a distributed transformer optimizer and a distillation toolkit designed to reduce denoising steps and model complexity to increase frame rates. The project distinguishes itself through specialized acceleration techniques, including joint distillation and sparse attention training. It implements low-step video generation and weight quantization to FP8 or FP4 precision to increase throughput a
Diffusers is a PyTorch-based library and generative AI framework used to build, train, and deploy diffusion pipelines for producing multi-modal media. It provides a suite of tools for generating images, video, and audio from natural language descriptions, as well as specialized systems for text-to-image generation. The project differentiates itself through a modular architecture that separates noise schedulers, pretrained model blocks, and pipeline compositions. This structure allows for the construction of custom generation workflows and the ability to swap individual components of the diffu
A general fine-tuning kit geared toward image/video/audio diffusion models.
