Instructions to use fal/LTX-2.3-FlashPack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/LTX-2.3-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-2.3-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:
- 5dd8b9db76068db459c676fecd8c868cd4362a437cc5328589aef1cbcf137085
- Size of remote file:
- 63.8 MB
- SHA256:
- 181625037a73df9d918a6b7f79fce9187fd95a13f4447664f88c1d1ad1bb8ff9
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