Update README.md

README.md

@@ -1,3 +1,41 @@
----
-license: mit
----
+---
+license: mit
+language:
+- en
+library_name: jax
+tags:
+- perturbation-prediction
+- prior-data-fitted-networks
+- in-context-learning
+- single-cell
+- causal-inference
+- diffusion-transformer
+datasets:
+- marvinsxtr/MapPFN
+pipeline_tag: other
+---
+
+# MapPFN Weights
+
+Pre-trained and fine-tuned checkpoints for [MapPFN: Learning Causal Perturbation Maps in Context](https://arxiv.org/abs/2601.21092) (Sextro et al., 2026).
+
+## Checkpoints
+
+- `model.ckpt` — Pre-trained on synthetic biological prior (50 dimensions, 400k steps)
+- `model_finetuned_frangieh.ckpt` — Fine-tuned on [Frangieh et al. (2021)](https://doi.org/10.1038/s41588-021-00779-1)
+- `model_finetuned_papalexi.ckpt` — Fine-tuned on [Papalexi et al. (2021)](https://doi.org/10.1038/s41588-021-00778-2)
+
+All checkpoints share the same MMDiT architecture (~25M parameters) and differ only in training data. See the [GitHub repository](https://github.com/marvinsxtr/MapPFN) for inference and fine-tuning code.
+
+## Citation
+
+```bibtex
+@article{sextro2026mappfn,
+  title   = {{MapPFN}: Learning Causal Perturbation Maps in Context},
+  author  = {Sextro, Marvin and K\l{}os, Weronika and Dernbach, Gabriel},
+  journal = {arXiv preprint arXiv:2601.21092},
+  year    = {2026}
+}
+```
+
+**Links:** [Paper](https://arxiv.org/abs/2601.21092) | [Code](https://github.com/marvinsxtr/MapPFN) | [Datasets](https://huggingface.co/datasets/marvinsxtr/MapPFN) | [Project Page](https://marvinsxtr.github.io/MapPFN)