Add model card for MeFEm

README.md

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+---
+pipeline_tag: image-feature-extraction
+---
+
+# MeFEm: Medical Face Embedding model
+
+MeFEm is a vision model based on a modified Joint Embedding Predictive Architecture (JEPA) for biometric and medical analysis from facial images.
+
+## Model Description
+
+MeFEm introduces several modifications to the JEPA framework to optimize for medical and biometric facial analysis:
+- **Axial stripe masking strategy**: Focuses learning on semantically relevant regions of the face.
+- **Circular loss weighting scheme**: A novel weighting approach for the training objective.
+- **Probabilistic reassignment of the CLS token**: Designed to improve the quality of linear probing for downstream tasks.
+
+The model was trained on a consolidated dataset of curated images and outperforms strong baselines like FaRL and Franca on core anthropometric tasks and Body Mass Index (BMI) estimation, despite using significantly less data.
+
+## Resources
+
+- **Paper**: [MeFEm: Medical Face Embedding model](https://huggingface.co/papers/2602.14672)
+
+## Citation
+
+```bibtex
+@article{mefem2026,
+  title={MeFEm: Medical Face Embedding model},
+  author={},
+  journal={arXiv preprint arXiv:2602.14672},
+  year={2026}
+}
+```