| 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 | |
| - text-to-image | |
| - diffusers | |
| - textual_inversion | |
| inference: true | |
| # Textual inversion text2image fine-tuning - hcarrion/abscess | |
| These are textual inversion adaptation weights for `stabilityai/stable-diffusion-2-1-base` to generate dermatological images representing the **abscess** class. | |
| This model was trained as part of the paper: | |
| **[Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification](https://huggingface.co/papers/2607.12987)** (MICCAI 2026). | |
| - **Code:** [hectorcarrion/ControllableGenDDI](https://github.com/hectorcarrion/ControllableGenDDI) | |
| - **Dataset:** [hcarrion/ControllableGenDDI](https://huggingface.co/datasets/hcarrion/ControllableGenDDI) | |
| ## Citation | |
| ```bibtex | |
| @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} | |
| } | |
| ``` |