Instructions to use ckpt/FLUX.1-dev-Controlnet-Inpainting-Alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ckpt/FLUX.1-dev-Controlnet-Inpainting-Alpha with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ckpt/FLUX.1-dev-Controlnet-Inpainting-Alpha", 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
File size: 135 Bytes
6af1296 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:0e9d4891bb416584228b8fe16f35154ee462870f3798c108eef199d826c63ee2
size 4281803800
|