Image-to-Video
Diffusers
Safetensors
world-model
video-generation
text-to-video
action-conditioned
causal
Instructions to use seedleap/zing-0.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use seedleap/zing-0.5 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("seedleap/zing-0.5", 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
Use full Zing logo in model card title
Browse files- README.md +1 -1
- assets/zing-logo.svg +28 -0
README.md
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- causal
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# <img src="https://huggingface.co/seedleap/zing-0.5/resolve/main/assets/zing-logo
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[Project Page](https://zing.loopit.me/) 路 [GitHub](https://github.com/seedleap/zing-world-model) 路 Technical Report (Coming soon)
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- causal
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# <img src="https://huggingface.co/seedleap/zing-0.5/resolve/main/assets/zing-logo.svg" alt="Zing" height="52" style="vertical-align: middle;"> <span style="font-size: 1.2em;">Zing-0.5: An Efficient Real-Time Interactive World Model</span>
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[Project Page](https://zing.loopit.me/) 路 [GitHub](https://github.com/seedleap/zing-world-model) 路 Technical Report (Coming soon)
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assets/zing-logo.svg
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