Enhance model card with metadata and usage example

README.md

@@ -1,3 +1,54 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+pipeline_tag: image-text-to-text
+library_name: transformers
+---
+
+This repository contains the official implementation of the paper: [Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image Analysis](https://huggingface.co/papers/2503.20047).
+
+Med3DVLM is a 3D VLM designed to address the challenges of 3D medical image analysis through efficient encoding, improved image-text alignment with a pairwise sigmoid loss, and a dual-stream MLP-Mixer projector for richer multi-modal representations. It achieves superior performance across multiple benchmarks including image-text retrieval, report generation, and open/closed-ended visual question answering.
+
+Code: https://github.com/mirthAI/Med3DVLM
+
+![Med3DVLM Architecture](https://github.com/mirthAI/Med3DVLM/raw/main/docs/pipeline.png)
+
+## Installation
+First, clone the repository to your local machine:
+```bash
+git clone https://github.com/mirthAI/Med3DVLM.git
+cd Med3DVLM
+```
+To install the required packages, you can use the following command:
+```bash
+conda create -n Med3DVLM -f env.yaml
+conda activate Med3DVLM
+```
+or
+```bash
+pip install -r requirements.txt
+```
+
+You need to set the `PYTHONPATH` environment variable to the root directory of the project. You can do this by running the following command in your terminal:
+
+```bash
+export PYTHONPATH=$(pwd):$PYTHONPATH
+```
+
+## Sample Usage
+
+To run a demo in the terminal, use the following command (replace `path_to_model` and `path_to_image` with your actual paths):
+
+```bash
+python scr/demo/demo.py --model_name_or_path path_to_model --image_path path_to_image --question "Describe the findings of the medical image you see."
+```
+
+## Citation
+If you use our code or find our work helpful, please consider citing our paper:
+```bibtex
+@article{xin2025med3dvlm,
+  title={Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image Analysis},
+  author={Xin, Yu and Ates, Gorkem Can and Gong, Kuang and Shao, Wei},
+  journal={IEEE Journal of Biomedical and Health Informatics},
+  year={2025}
+}
+```