Instructions to use black-forest-labs/FLUX.1-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use black-forest-labs/FLUX.1-dev with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
how can flux support controlnet , like openpose, canny.... ?
#22
by huangzx111 - opened
how can flux support controlnet , like openpose, canny...
It's not ready for that yet. I hope we get it soon
Flux Controlnet Collections
https://huggingface.co/XLabs-AI/flux-controlnet-collections
Our collection supports 3 models:
- Canny
- HED
- Depth (Midas)
Each ControlNet is trained on 1024x1024 resolution. However, we recommend you to generate images with 1024x1024 for Depth, and use 768x768 resolution for Canny and HED for better results.