Instructions to use Dhanidjulian/LTX-Video-0.9.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Dhanidjulian/LTX-Video-0.9.5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Dhanidjulian/LTX-Video-0.9.5", 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:
- aa7c4d3a195b37c0ad1c30561fd16d93ee8293a9b1f475f86de2690f761018fd
- Size of remote file:
- 7.47 MB
- SHA256:
- 39790832fd9bff62c99a799eb4843cf99c9ab73c3f181656acbbd0d4ebf7f471
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