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
Download diffusion_pytorch_model.safetensors from fal/FLUX.2-Tiny-AutoEncoder: direct link, hf CLI and curl.
- Browser
- Download file 5.86 MB
-
https://huggingface.co/fal/FLUX.2-Tiny-AutoEncoder/resolve/main/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://fal/FLUX.2-Tiny-AutoEncoder/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/fal/FLUX.2-Tiny-AutoEncoder/resolve/main/diffusion_pytorch_model.safetensors
5.86 MB
- Xet hash:
- 7b0c44c85f4b3a9a137a0581c02ed1690f4bc7cab148b4f5db649151a47c0897
- Size of remote file:
- 5.86 MB
- SHA256:
- 16e3100fee8a4046015b7440b2e4384755c9fde146bf44634ff4fe763205b38f
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