Instructions to use DDUF/FLUX.1-dev-DDUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DDUF/FLUX.1-dev-DDUF with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DDUF/FLUX.1-dev-DDUF", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7f07226f4ecd82f8b5090856d026857d5d6dae2ec7d1c0fb483f713754d806c
- Size of remote file:
- 33.7 GB
- SHA256:
- 8ecd09a0334b7372e16281eb2f663def533978668c8e50c688a06202fb806180
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