Instructions to use Ziyaad30/ltxv0.9.8-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ziyaad30/ltxv0.9.8-decoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Ziyaad30/ltxv0.9.8-decoder", 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:
- 5eef54ba8080a7441614d2462e831c37974c91b3924fb6c34ba0ef3b59e21934
- Size of remote file:
- 2.49 GB
- SHA256:
- 3419989c7059923ee4134b858e0511d0b294a7c88b7745169763b37ebc4db7f0
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