Instructions to use robbyant/lingbot-world-fast-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use robbyant/lingbot-world-fast-diffusers 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("robbyant/lingbot-world-fast-diffusers", 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 assets/teaser.png from robbyant/lingbot-world-fast-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 5.45 MB
-
https://huggingface.co/robbyant/lingbot-world-fast-diffusers/resolve/main/assets/teaser.png
- Command line
-
hf download hf://robbyant/lingbot-world-fast-diffusers/assets/teaser.png
-
curl -L -o teaser.png https://huggingface.co/robbyant/lingbot-world-fast-diffusers/resolve/main/assets/teaser.png
5.45 MB

- Xet hash:
- 3fe9caae56e80396258d69f4798298dba76ea51e4bbe698166df28223f3514f7
- Size of remote file:
- 5.45 MB
- SHA256:
- 5a5534584d6b2c42ce445930787b6a6784cf9c2d6ed4d1a78c7be3d8e15bed73
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