Update README.md

README.md

@@ -1,9 +1,49 @@
 ---
-metrics:
-- bertscore
-library_name: transformers
-pipeline_tag: summarization
+language: en
 tags:
-- medical
 - summarization
----
+- medical
+library_name: transformers
+pipeline_tag: summarization
+---
+
+# Automatic Personalized Impression Generation for PET Reports Using Large Language Models 📄✍
+
+**Authored by**: Xin Tie, Muheon Shin, Ali Pirasteh, Nevein Ibrahim, Zachary Huemann, Sharon M. Castellino, Kara Kelly, John Garrett, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw
+
+[Read the full paper]()
+<!-- Link to our Arxiv paper -->
+
+## 📑 Model Description
+
+This is the domain-adapted BARTScore for evaluating the quality of PET impressions. 
+
+To check our fine-tuned large language models (LLMs) for PET report summarization: 
+- [BARTScore+PET](https://huggingface.co/xtie/BARTScore-PET)
+- [PEGASUSScore+PET](https://huggingface.co/xtie/PEGASUSScore-PET)
+- [T5+PET](https://huggingface.co/xtie/T5Score-PET)
+
+
+
+## 🚀 Usage
+
+Clone this GitHub repository in a local folder
+```bash
+git clone https://github.com/xtie97/PET-Report-Summarization.git
+```
+
+Go the the folder containing codes for computing BARTScore and create a new folder called "checkpoints"
+```bash
+cd ./PET-Report-Summarization/evaluation_metrics/metrics/BARTScore
+mkdir checkpoints
+mkdir checkpoints/bart-large
+```
+
+Download the model weights and put them in the folder "checkpoints/bart-large". Run the code for computing text-generation-based metrics 
+```
+python compute_metrics_text_generation.py
+```
+
+## 📁 Additional Resources
+- **Codebase for evaluation metrics:** [GitHub Repository](https://github.com/xtie97/PET-Report-Summarization)
+---