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:
- 4faa812120216281af5deec0eb572e18c9541067366038af1a8cdbfa10c02fc2
- Size of remote file:
- 11.7 MB
- SHA256:
- f0fb2c15137bba77b3dbfd5f68e31ff9410bbb6873cee4f50b1ce2c4d6978b62
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.