|
--- |
|
license: apache-2.0 |
|
--- |
|
|
|
|
|
<p align="center"> |
|
<img src="https://cdn-uploads.huggingface.co/production/uploads/63993d721fad4d6eb265d999/UXleJWJExX2WlBizxzYxn.png" width="250"/> |
|
</p> |
|
|
|
|
|
# Open-Sora STDiT-v3 Weights |
|
|
|
This repository stores the weights of the VAE released by the Open-Sora team. You can visit our project at: |
|
|
|
- [GitHub](https://github.com/hpcaitech/Open-Sora) |
|
- [Gallery](https://hpcaitech.github.io/Open-Sora/) |
|
- [Gradio Demo](https://huggingface.co./spaces/hpcai-tech/open-sora) |
|
|
|
We recommend you to use this weights in the [Open-Sora codebase]((https://github.com/hpcaitech/Open-Sora)). If you want to use VAE in your own project, you may use the following sample code. |
|
|
|
1. Install `opensora` |
|
|
|
```bash |
|
pip install git+https://github.com/hpcaitech/Open-Sora.git |
|
``` |
|
|
|
2. Use `STDiT3` in your own code |
|
|
|
```python |
|
from opensora.models.vae.vae import VideoAutoencoderPipeline |
|
vae = VideoAutoencoderPipeline.from_pretrained("hpcai-tech/OpenSora-VAE-v1.2") |
|
``` |