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
Link model to paper and code repository
Browse filesHi! I'm Niels from the Hugging Face community science team.
This PR improves the model card for your textual inversion model:
- Sets the `pipeline_tag` to `text-to-image` and the `library_name` to `diffusers` in the YAML metadata.
- Links the model card to the corresponding paper: [Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification](https://huggingface.co/papers/2607.12987).
- Adds a link to the official GitHub repository and dataset for easier access.
Feel free to merge if this looks good to you!
README.md
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---
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license: creativeml-openrail-m
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base_model: stabilityai/stable-diffusion-2-1-base
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- text-to-image
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- diffusers
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- textual_inversion
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inference: true
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---
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# Textual inversion text2image fine-tuning - hcarrion/hyperpigmentation
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These are textual inversion adaption weights for stabilityai/stable-diffusion-2-1-base. You can find some example images in the following.
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---
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base_model: stabilityai/stable-diffusion-2-1-base
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library_name: diffusers
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license: creativeml-openrail-m
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pipeline_tag: text-to-image
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- diffusers
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- textual_inversion
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inference: true
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---
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# cgDDI: Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification
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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](https://huggingface.co/papers/2607.12987).
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* **Code:** [GitHub - ControllableGenDDI](https://github.com/hectorcarrion/ControllableGenDDI)
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* **Dataset:** [hcarrion/ControllableGenDDI](https://huggingface.co/datasets/hcarrion/ControllableGenDDI)
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## Citation
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If you find this work useful in your research, please cite:
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```bibtex
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@inproceedings{carrion2026cgddi,
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title = {Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification},
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author = {Carri{\'o}n, H{\'e}ctor and Norouzi, Narges},
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booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
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year = {2026},
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publisher = {Springer},
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series = {Lecture Notes in Computer Science}
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}
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```
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