Instructions to use tensorart/SD3.5M-Controlnet-Depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tensorart/SD3.5M-Controlnet-Depth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tensorart/SD3.5M-Controlnet-Depth", 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
Update README.md
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README.md
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@@ -54,7 +54,7 @@ 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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"
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controlnet=controlnet
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)
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pipe.to("cuda", torch.float16)
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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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