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--- |
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license: other |
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license_name: stabilityai-ai-community |
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license_link: LICENSE.md |
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language: |
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- en |
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base_model: |
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- stabilityai/stable-diffusion-3.5-medium |
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pipeline_tag: text-to-image |
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--- |
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<div align="center"> |
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**TensorArt Stable Diffusion 3.5 Medium ControlNet Depth** |
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<img src="./asset/demo.png"/> |
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</div> |
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# With SD3.5M |
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```python |
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import torch |
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from diffusers import StableDiffusion3ControlNetPipeline |
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from diffusers import SD3ControlNetModel |
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from diffusers.utils import load_image |
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controlnet = SD3ControlNetModel.from_pretrained("tensorart/SD3.5M-Controlnet-Depth") |
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pipe = StableDiffusion3ControlNetPipeline.from_pretrained( |
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"stabilityai/stable-diffusion-3.5-medium", |
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controlnet=controlnet |
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) |
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pipe.to("cuda", torch.float16) |
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control_image = load_image("https://huggingface.co/tensorart/SD3.5M-Controlnet-Depth/resolve/main/asset/depth.png") |
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prompt = "A cyberpunk man" |
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negative_prompt = "low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, monochrome" |
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image = pipe( |
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prompt, |
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num_inference_steps=30, |
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negative_prompt=negative_prompt, |
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control_image=control_image, |
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guidance_scale=4.5, |
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).images[0] |
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image.save('image.jpg') |
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``` |
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# With TensorArt's SD3.5M Turbo |
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```python |
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import torch |
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from diffusers import StableDiffusion3ControlNetPipeline |
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from diffusers import SD3ControlNetModel |
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from diffusers.utils import load_image |
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controlnet = SD3ControlNetModel.from_pretrained("tensorart/SD3.5M-Controlnet-Depth") |
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pipe = StableDiffusion3ControlNetPipeline.from_pretrained( |
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"tensorart/stable-diffusion-3.5-medium-turbo", |
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controlnet=controlnet |
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) |
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pipe.to("cuda", torch.float16) |
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control_image = load_image("https://huggingface.co/tensorart/SD3.5M-Controlnet-Depth/resolve/main/asset/depth.png") |
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prompt = "A cyberpunk man" |
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negative_prompt = "low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, monochrome" |
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image = pipe( |
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prompt, |
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num_inference_steps=8, |
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negative_prompt=negative_prompt, |
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control_image=control_image, |
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guidance_scale=1.5 |
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).images[0] |
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image.save('image.jpg') |
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``` |
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## Contact |
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* Website: https://tensor.art https://tusiart.com |
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* Developed by: TensorArt |
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