Instructions to use models123/FLUX.2-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use models123/FLUX.2-dev 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("models123/FLUX.2-dev", 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:
- 16d542e196781d7e982a944e2950bb4cae0b32c55d4c31449c8ad63415d4e871
- Size of remote file:
- 23.3 MB
- SHA256:
- 4df742c27729c240828ca676401f9bbee20ce1baa1b8868b7e50ead7f837d61a
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