| --- |
| language: |
| - en |
| license: mit |
| --- |
| |
| This repository contains LoRA weights and requires the Flux.1 base model. |
| Use of this model is subject to the license of the base model. |
|
|
|
|
| # Model Description |
|
|
| DermaFlux LoRA is a parameter-efficient fine-tuning of the Flux.1 text-to-image model designed to generate clinically grounded skin lesion images from structured natural language prompts. |
| The model enables synthesis of dermatology images conditioned on clinically relevant attributes such as: |
|
|
| - lesion asymmetry |
| - border irregularity |
| - color variation |
|
|
| The goal of the model is to augment dermatology datasets with realistic synthetic samples to improve downstream tasks such as skin lesion classification. |
| The LoRA weights modify the base Flux.1 generative model without requiring full model retraining. |
|
|
| # Installation |
|
|
| The environment setup and inference scripts are provided in the official repository: |
|
|
| [https://github.com/dermaflux/dermaflux](https://github.com/dermaflux/dermaflux) |
|
|
| Please follow the installation instructions in the repository to create the required environment and install the dependencies. |
|
|
| The repository includes: |
|
|
| - environment setup instructions |
| - required Python packages |
| - inference script for running the model |
|
|
| After setting up the environment, download the LoRA weights from this Hugging Face repository and use them with the inference code provided in the GitHub repository. |
|
|
| # Citation |
|
|
| If you use this model, please cite the DermaFlux paper: |
| ```bibtex |
| @misc{galanakis2026dermafluxsyntheticskinlesion, |
| title={DermaFlux: Synthetic Skin Lesion Generation with Rectified Flows for Enhanced Image Classification}, |
| author={Stathis Galanakis and Alexandros Koliousis and Stefanos Zafeiriou}, |
| year={2026}, |
| eprint={2603.16392}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2603.16392}, |
| } |
| ``` |
