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 video_decoder/model.flashpack from fal/LTX-2-FlashPack: direct link, hf CLI and curl.
- Browser
- Download file 1.06 GB
-
https://huggingface.co/fal/LTX-2-FlashPack/resolve/main/video_decoder/model.flashpack
- Command line
-
hf download hf://fal/LTX-2-FlashPack/video_decoder/model.flashpack
-
curl -L -o model.flashpack https://huggingface.co/fal/LTX-2-FlashPack/resolve/main/video_decoder/model.flashpack
1.06 GB
- Xet hash:
- 86d2a9a9e06bc4bfe9f638066fb1d5cf2002b97eefffb02b056225815da3527f
- Size of remote file:
- 1.06 GB
- SHA256:
- d2beb5bf1ad08496741eeb5de80cbfa9225d99b0464bc8f542f030661c70e62c
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