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:
- f15b7afe174e3c9ce48228abe4e2e78e57e18ea9d24dc70ffb8823a91362850e
- Size of remote file:
- 1.39 MB
- SHA256:
- c3f25e740605290335fc91552e118ae0973e1c7b8964c27e05884e6bce962e62
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