Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
Instructions to use hcarrion/hyperpigmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hcarrion/hyperpigmentation 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/hyperpigmentation") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from hcarrion/hyperpigmentation: direct link, hf CLI and curl.
- Browser
- Download file 1.4 kB
-
https://huggingface.co/hcarrion/hyperpigmentation/resolve/main/README.md
- Command line
-
hf download hf://hcarrion/hyperpigmentation/README.md
-
curl -L -o README.md https://huggingface.co/hcarrion/hyperpigmentation/resolve/main/README.md
1.4 kB
metadata
base_model: stabilityai/stable-diffusion-2-1-base
library_name: diffusers
license: creativeml-openrail-m
pipeline_tag: text-to-image
tags:
- stable-diffusion
- stable-diffusion-diffusers
- diffusers
- textual_inversion
inference: true
cgDDI: Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification
This repository contains the textual inversion adaptation weights for stabilityai/stable-diffusion-2-1-base corresponding to the hyperpigmentation disease concept, as presented in the paper Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification.
- Code: GitHub - ControllableGenDDI
- Dataset: hcarrion/ControllableGenDDI
Citation
If you find this work useful in your research, 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}
}