Instructions to use black-forest-labs/FLUX.1-Canny-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-Canny-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-Canny-dev", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use black-forest-labs/FLUX.1-Canny-dev with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Multiple controlnets?
Is it possible to use both canny and depth at the same time? This appears to be different than the Shakker-Labs controlnets (and others) in that it seems to not be a drop in replacement in the same pipeline.
Would like to know as well.
You can combine Black Forest Labs ControlNets with a dual sampler Flux workflow. This uses SamplerCustomAdvanced nodes and a SplitSigmas node, but the quality of the canny model is so poor that there's no reason to.
https://www.reddit.com/r/comfyui/comments/1d1x5ek/dual_prompting_with_split_sigmas/
The depth model works ok, but the canny model only adds more blocky pixelated noise.