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
- Draw Things
- DiffusionBee
- Xet hash:
- c504686a19e8ecbfd7d87dc780221853c36ff88ce792e8ae74704989be883f1f
- Size of remote file:
- 23.8 GB
- SHA256:
- b48435d7cd6639d1ed7ff5c2608fdbc12dbbdb42f589d7b014a2e292dbde7aae
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