Text-to-Image
Diffusers
Safetensors
English
Text-to-Image
ControlNet
Diffusers
Flux.1-dev
image-generation
Stable Diffusion
Instructions to use Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro", 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
- Local Apps
- Draw Things
- DiffusionBee
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This repository contains an unified ControlNet for FLUX.1-dev model jointly released by researchers from [InstantX Team](https://huggingface.co/InstantX) and [Shakker Labs](https://huggingface.co/Shakker-Labs).
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# Model Cards
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- This checkpoint is a Pro version of [FLUX.1-dev-Controlnet-Union](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union) trained with more steps and datasets.
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- This model supports 7 control modes, including canny (0), tile (1), depth (2), blur (3), pose (4), gray (5), low quality (6).
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This repository contains an unified ControlNet for FLUX.1-dev model jointly released by researchers from [InstantX Team](https://huggingface.co/InstantX) and [Shakker Labs](https://huggingface.co/Shakker-Labs).
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<div class="container">
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<img src="./assets/poster.png" width="1024"/>
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</div>
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# Model Cards
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- This checkpoint is a Pro version of [FLUX.1-dev-Controlnet-Union](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union) trained with more steps and datasets.
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- This model supports 7 control modes, including canny (0), tile (1), depth (2), blur (3), pose (4), gray (5), low quality (6).
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