Instructions to use onkarsus13/Semantic-Control-Stable-diffusion-3-M-Mask2CT-Atlas with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use onkarsus13/Semantic-Control-Stable-diffusion-3-M-Mask2CT-Atlas with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("onkarsus13/Semantic-Control-Stable-diffusion-3-M-Mask2CT-Atlas", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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For Pretraining we used Atlas Dataset From John Hopkins
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Training Details
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Image Size = (128, 128)
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Batch_size = 8 x 28 x 12
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Computes:
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8 x Nvidia-A6000 48GB
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Code for generation:
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For Pretraining we used Atlas Dataset From John Hopkins
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```
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Training Details
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Image Size = (128, 128)
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Batch_size = 8 x 28 x 12
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Computes:
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8 x Nvidia-A6000 48GB
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```
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Code for generation:
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