Instructions to use diffusers-modular/MiniMax-H3-LightVAE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-modular/MiniMax-H3-LightVAE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers-modular/MiniMax-H3-LightVAE", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Download vae/diffusion_pytorch_model.safetensors from diffusers-modular/MiniMax-H3-LightVAE: direct link, hf CLI and curl.
- Browser
- Download file 3.65 GB
-
https://huggingface.co/diffusers-modular/MiniMax-H3-LightVAE/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://diffusers-modular/MiniMax-H3-LightVAE/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/diffusers-modular/MiniMax-H3-LightVAE/resolve/main/vae/diffusion_pytorch_model.safetensors
3.65 GB
- Xet hash:
- 7aa3c3d6d789f6eaf06c4ad088e94a6d9f5383cde80810be78d5f925f879ea68
- Size of remote file:
- 3.65 GB
- SHA256:
- bccba90f8dfd77cd446e965d70596ab0d52d60a620d5867ddcbdbb7d4f857f6e
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