Instructions to use RockSky1/Bleza-Video with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RockSky1/Bleza-Video with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RockSky1/Bleza-Video", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download vae/diffusion_pytorch_model.bin from RockSky1/Bleza-Video: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/RockSky1/Bleza-Video/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://RockSky1/Bleza-Video/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/RockSky1/Bleza-Video/resolve/main/vae/diffusion_pytorch_model.bin
167 MB
- Xet hash:
- 56319e3949c11c8f8d86fb3d49731f896a30a180a8d9b607b50ee84bff935937
- Size of remote file:
- 167 MB
- SHA256:
- 8b0d11ff25d00ceaa02f602831d9cfe650509fdc850c0a1bcb2acdfa03bd5d56
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