Improve model card: add paper link, GitHub link, and summary

README.md

@@ -1,7 +1,8 @@
 ---
-license: apache-2.0
 language:
 - en
+license: apache-2.0
+pipeline_tag: image-feature-extraction
 tags:
 - cytology
 - hematology
@@ -10,14 +11,25 @@ tags:
 - pytorch
 - self-supervised
 - vit
-pipeline_tag: image-feature-extraction
 ---
 
-
 # GenBloom
 
-This repository contains the model weights used for the public visual
-downstream reproduction.
+[GenBloom](https://huggingface.co/papers/2605.29980) is a genetically-aligned foundation model for peripheral blood smears. It aligns single white blood cell images with chromosomal aberrations (karyotype) and somatic mutations from targeted gene panels.
+
+For the source code, setup, and evaluation scripts, see the [GenBloom GitHub repository](https://github.com/marrlab/GenBloom).
+
+## Model Description
+
+GenBloom is a patient-level encoder trained using a two-stage approach:
+1. **GenBloom-V (Self-supervised Pretraining)**: Vision-only pretraining of a transformer aggregator using an iBOT head on a cohort of over 1,500 patients.
+2. **GenBloom-G (Genetic Alignment)**: Further alignment of visual features with chromosomal aberrations and somatic mutations via supervised contrastive loss on acute myeloid leukemia patients.
+
+The model provides improved representations for hematological diagnostic tasks and provides off-the-shelf retrieval capabilities for diseases and genetic alterations.
+
+## Checkpoints
+
+This repository contains the model weights used for the public visual downstream reproduction:
 
 ```text
 checkpoints/
@@ -31,6 +43,32 @@ checkpoints/
     genbloom_g_fold4.pth
 ```
 
-The `genbloom_v` checkpoint corresponds to image-only pretraining. The `genbloom_g` checkpoints were further genetically aligned.
+- The `genbloom_v` checkpoint corresponds to image-only pretraining. 
+- The `genbloom_g` checkpoints were further genetically aligned.
+
+## Usage
+
+### Download Checkpoints
+You can download the checkpoints using the `huggingface_hub` library:
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download("MarrLab/GenBloom", local_dir="checkpoints")
+```
+
+### Inference
+A minimal end-to-end inference example is available in the [`inference_genbloom.ipynb`](https://github.com/marrlab/GenBloom/blob/main/inference_genbloom.ipynb) notebook in the official repository.
+
+## Citation
+
+If you use GenBloom in your research, please cite:
 
-For the source code, see the [GenBloom GitHub repository](https://github.com/marrlab/GenBloom)
+```bibtex
+@article{genbloom2024,
+  title={Genetically Aligned Patient Representations Improve Hematological Diagnosis},
+  author={Adelpantidis, Georgios and others},
+  journal={arXiv preprint arXiv:2605.29980},
+  year={2024}
+}
+```