Instructions to use hf-internal-testing/tiny-LTX2Pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-LTX2Pipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-LTX2Pipeline", 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:
- 1af9c7e75117764706a0b92325516f9092d5227038dbccbacac3be49dfac8f12
- Size of remote file:
- 34.4 MB
- SHA256:
- 2f2b2e38ee7aced4b332a26484feae78e3d809c0cec32b1bb2a50e62962d0614
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