Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification
Paper • 2607.12987 • Published
How to use hcarrion/squamous_cell_carcinoma with Diffusers:
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/squamous_cell_carcinoma")This repository contains the textual inversion adaptation weights for stabilityai/stable-diffusion-2-1-base representing the squamous cell carcinoma disease concept.
It was trained as part of the framework introduced in the paper Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification.
If you use these weights or find this work useful, please cite:
@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}
}
Base model
stabilityai/stable-diffusion-2-1-base