How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda")
pipe.load_textual_inversion("hcarrion/dermatomyositis")

cgDDI: Dermatomyositis Textual Inversion Weights

These are the textual inversion adaptation weights for stabilityai/stable-diffusion-2-1-base trained on the "dermatomyositis" disease concept.

This model is part of the cgDDI (Controllable Generation of Diverse Dermatological Imagery) framework introduced in the paper: Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification.

Citation

@inproceedings{carrion2026cgddi,
  title     = {Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification},
  author    = {Carri{\\'o}n, H{\\'e}ctor and Norouzi, Narges},
  booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
  year      = {2026},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science}
}
Downloads last month
14
Safetensors
Model size
0.9B params
Tensor type
F16
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for hcarrion/dermatomyositis

Adapter
(713)
this model

Paper for hcarrion/dermatomyositis