Instructions to use fal/FLUX.2-Tiny-AutoEncoder-FlashPack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/FLUX.2-Tiny-AutoEncoder-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/FLUX.2-Tiny-AutoEncoder-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:
- 61b634adcdcf43ac0d8bf3b86e5777cdb3b1a3ecdbef6cd48ef72d8740cc28eb
- Size of remote file:
- 5.86 MB
- SHA256:
- db1cb216f9e9f86fccd53a259c2155ced8cd25a00907e05afadf81f6236de43d
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