Instructions to use fal/FLUX.2-Tiny-AutoEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/FLUX.2-Tiny-AutoEncoder 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", 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
Commit History
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Add Diffusers AutoModel support (#1)
Verified signature- Add Diffusers AutoModel support (e244d68e1c2a5ef1e1c6694e012ee4eff9fe4719) - Upload README.md with huggingface_hub (e6d2e0a769c64418587c63f0c04ec20e7356f054) - Upload README.md with huggingface_hub (53782045bea36ee193c604b11e342790750d776a) - Upload README.md with huggingface_hub (f0dc16f111a3d8318ab8fbe38b666c62de6dc3f2) Co-authored-by: Dhruv Nair <dn6@users.noreply.huggingface.co>9f80e4d
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