Instructions to use fal/LTX-2-FlashPack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/LTX-2-FlashPack with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fal/LTX-2-FlashPack", 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:
- 9d70a250ae5d3e80a37c627fc16700b924dbad7d7b3b8a2c5d673d24a285e73a
- Size of remote file:
- 996 MB
- SHA256:
- 6d4a3dfc17ad2f2433c9d1221b8a0e6326539b478475fa1de71303a53f51c329
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.