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:
- a1b424f123ef4c9d92e709de5083986d668c62d04d6f1aee60fceebc19fab9f1
- Size of remote file:
- 13.4 kB
- SHA256:
- a86c1d8d653163146e3e1c6e5f4365ba23edb41993640b9f4458d39950862610
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