Update README.md

README.md

@@ -4,3 +4,74 @@ language: multilingual
 library_name: transformers
 license: cc-by-nc-sa-4.0
 ---
+
+<div align="center">
+
+<h1 style="font-family: 'Arial', sans-serif; font-size: 28px; font-weight: bold; color: black;">
+    🛡️ Guardians of the Machine Translation Meta-Evaluation:<br>
+    Sentinel Metrics Fall In!
+</h1>
+
+</div>
+
+<div style="display:flex; justify-content: center; align-items: center; flex-direction: row;">
+    <a href="https://2024.aclweb.org/"><img src="http://img.shields.io/badge/ACL-2024-4b44ce.svg"></a> &nbsp; &nbsp; 
+    <a href="https://aclanthology.org/"><img src="http://img.shields.io/badge/paper-ACL--anthology-B31B1B.svg"></a> &nbsp; &nbsp; 
+    <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/"><img src="https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg"></a>
+</div>
+<div style="display:flex; justify-content: center; align-items: center; flex-direction: row;">
+    <a href="https://huggingface.co/collections/sapienzanlp/mt-sentinel-metrics-66ab643b32aab06f3157e5c1"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Collection-FCD21D"></a> &nbsp; &nbsp;
+    <a href="https://github.com/SapienzaNLP/guardians-mt-eval"><img src="https://img.shields.io/badge/GitHub-Repo-121013?logo=github&logoColor=white"></a> &nbsp; &nbsp;
+</div>
+
+This repository contains the **SENTINEL<sub>CAND</sub>** metric model trained on Direct Assessments (DA) annotations. For details on how to use our sentinel metric models, check our [GitHub repository](https://github.com/SapienzaNLP/guardians-mt-eval).
+
+## Usage
+
+After having installed our repository package, you can use this model within Python in the following way:
+
+```python
+from sentinel_metric import download_model, load_from_checkpoint
+
+model_path = download_model("sapienzanlp/sentinel-cand-da")
+model = load_from_checkpoint(model_path)
+
+data = [
+    {"mt": "There's no place like home."},
+    {"mt": "Toto, I've a feeling we're not in Kansas anymore."}
+]
+
+output = model.predict(data, batch_size=8, gpus=1)
+```
+
+Output:
+```python
+# Segment scores
+>>> output.scores
+[0.6060712337493896, 0.4322320222854614]
+
+# System score
+>>> output.system_score
+0.5191516280174255
+```
+
+## Cite this work
+This work has been published at [ACL 2024 (main conference)](https://2024.aclweb.org/program/main_conference_papers/). If you use any part, please consider citing our paper as follows:
+
+```bibtex
+@inproceedings{perrella-etal-2024-guardians,
+    title = "Guardians of the Machine Translation Meta-Evaluation: Sentinel Metrics Fall In!",
+    author = "Perrella, Stefano and
+      Proietti, Lorenzo  and
+      Scirè, Alessandro and
+      Barba, Edoardo and
+      Navigli, Roberto",
+        booktitle = "Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2024)",
+    year      = "2024",
+    address   = "Bangkok, Thailand",
+    publisher = "Association for Computational Linguistics",
+}
+```
+
+## License
+This work is licensed under [Creative Commons Attribution-ShareAlike-NonCommercial 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).