Text2Video:开源一键文生视频
Text2Video:开源一键文生视频 34,364 Stars | Apache-2.0 | Python <!--- Copyright 2022 -
Gana · 2026-08-23 · 6 分钟阅读Text2Video:开源一键文生视频
34,364 Stars | Apache-2.0 | Python
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<p align="center"> <br> <img src="https://raw.githubusercontent.com/huggingface/diffusers/main/docs/source/en/imgs/diffusers_library.jpg" width="400"/> <br> <p> <p align="center"> <a href="https://github.com/huggingface/diffusers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/datasets.svg?color=blue"></a> <a href="https://github.com/huggingface/diffusers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release
🤗 Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you're looking for a simple inference solution or training your own diffusion models, 🤗 Diffusers is a modular toolbox that supports both. Our library is designed with a focus on usability over performance, simple over easy, and customizability over abstractions.
🤗 Diffusers offers three core components:
- State-of-the-art diffusion pipelines that can be run in inference with just a few lines of code.
- Interchangeable noise schedulers for different diffusion speeds and output quality.
- Pretrained models that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems.
简介
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
相关标签
deep-learning · diffusion · flux · image-generation · image2image · image2video · latent-diffusion-models · pytorch
