Instructions to use Moqi27/FLUX.2-small-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Moqi27/FLUX.2-small-decoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Moqi27/FLUX.2-small-decoder", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Diffusion Single File
How to use Moqi27/FLUX.2-small-decoder with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 984e1ad92d97b73526c6f7474511c68608f77bbe215d1568179cede6b1ada8e2
- Size of remote file:
- 3.54 MB
- SHA256:
- ea01b25d80d35f3d0d0405c1f892477dfd65f2330c72bb763d59541b8f2d3679
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