Instructions to use onkarsus13/ControlNet-Stable-Diffusion-3-Medium-Mask2MRI-AMOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use onkarsus13/ControlNet-Stable-Diffusion-3-Medium-Mask2MRI-AMOS with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("onkarsus13/ControlNet-Stable-Diffusion-3-Medium-Mask2MRI-AMOS", 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
File size: 327 Bytes
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license: mit
library_name: diffusers
pipeline_tag: image-to-text
tags:
- medical
---
This Model is first pre-trained on the ATLAS dataset, Then we further finetuned on the AMOS MRI set.
You can find the pre-trained model here
```
https://huggingface.co/onkarsus13/Semantic-Control-Stable-diffusion-3-M-Mask2CT-Atlas
```
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