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--- |
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license: other |
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license_name: flux-1-dev-non-commercial-license |
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license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md |
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tags: |
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- Text-to-Image |
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- ControlNet |
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- Diffusers |
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- Stable Diffusion |
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base_model: black-forest-labs/FLUX.1-dev |
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--- |
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# FLUX.1-dev Controlnet |
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We have completed the training of the first version. |
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The training was conducted with a total pixel count of `1024*1024` at multi-scale. |
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We trained for 30k steps using a batch size of 8*8. |
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<img src="./images/image_demo.jpg" width = "800" /> |
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<img src="./images/image_demo_weight.png" width = "800" /> |
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# Diffusers version |
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Please ensure that you have installed the latest version of [Diffusers](https://github.com/huggingface/diffusers). |
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# Demo |
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```python |
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import torch |
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from diffusers.utils import load_image |
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from diffusers.pipelines.flux.pipeline_flux_controlnet import FluxControlNetPipeline |
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from diffusers.models.controlnet_flux import FluxControlNetModel |
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base_model = 'black-forest-labs/FLUX.1-dev' |
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controlnet_model = 'InstantX/FLUX.1-dev-Controlnet-Canny' |
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controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=torch.bfloat16) |
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pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16) |
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pipe.to("cuda") |
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control_image = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny/resolve/main/canny.jpg") |
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prompt = "A girl in city, 25 years old, cool, futuristic" |
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image = pipe( |
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prompt, |
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control_image=control_image, |
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controlnet_conditioning_scale=0.6, |
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num_inference_steps=28, |
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guidance_scale=3.5, |
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).images[0] |
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image.save("image.jpg") |
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``` |
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