Instructions to use leafspark/sv4d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use leafspark/sv4d with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("leafspark/sv4d", 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

- Xet hash:
- 9557c2bd847e2c255d60ba626b1cb0fbbd950f199f88e9455637a00b3523ab31
- Size of remote file:
- 8.37 MB
- SHA256:
- 0229b56ce0e4c1b97630384eb8d247fca2050cdcaa19c091d89aabc61edd227a
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