Instructions to use diffusers/FLUX.2-dev-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/FLUX.2-dev-bnb-4bit 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("diffusers/FLUX.2-dev-bnb-4bit", 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d761ba3514ea22426e213221c9780894c3c25afcd0f1a693b8dbcdc3d01baa60
- Size of remote file:
- 8.13 GB
- SHA256:
- 43bf95cffd68187b9e2097f11f80295433661ff8654d09413c27d1ad87c30107
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