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
Download audio_encoder/model.flashpack from fal/LTX-2-FlashPack: direct link, hf CLI and curl.
- Browser
- Download file 42.7 MB
-
https://huggingface.co/fal/LTX-2-FlashPack/resolve/main/audio_encoder/model.flashpack
- Command line
-
hf download hf://fal/LTX-2-FlashPack/audio_encoder/model.flashpack
-
curl -L -o model.flashpack https://huggingface.co/fal/LTX-2-FlashPack/resolve/main/audio_encoder/model.flashpack
42.7 MB
- Xet hash:
- 4dcf49a628373f5f69cd84738662570b5e3712c1d2373700d39d46829bfc8a23
- Size of remote file:
- 42.7 MB
- SHA256:
- 9355fcadfd68fbc45c926eec828fb59a712b1e04260fa894cb27e0baada4d4be
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.