Instructions to use sayakpaul/FLUX.1-dev-edit-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sayakpaul/FLUX.1-dev-edit-v0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sayakpaul/FLUX.1-dev-edit-v0", dtype=torch.bfloat16, device_map="cuda") prompt = "Give this the look of a traditional Japanese woodblock print." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- bd83b3a401d6cd2135358c6867499cb8511e79a84c15c1b159599287b801a2bd
- Size of remote file:
- 3.42 MB
- SHA256:
- 0574bdf0c90365ab7ae638051afaabf5b96d22bfcc149d401a19741136e0ce42
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