Improve model card with Github repository link (#1)

- Improve model card with Github repository link (293035534b87e93f91e4746327dcbca1becfa236)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,11 +1,15 @@
 ---
-license: apache-2.0
-language:
-- en
-library_name: gliner
+base_model:
+- microsoft/deberta-v3-small
 datasets:
 - knowledgator/GLINER-multi-task-synthetic-data
 - knowledgator/biomed_NER
+language:
+- en
+library_name: gliner
+license: apache-2.0
+metrics:
+- f1
 pipeline_tag: token-classification
 tags:
 - NER
@@ -14,13 +18,14 @@ tags:
 - encoder
 - entity recognition
 - biomed
-base_model:
-- microsoft/deberta-v3-small
-metrics:
-- f1
 ---
+
 # GLiNER-BioMed
 
+The model was presented in the paper [GLiNER-biomed: A Suite of Efficient Models for Open Biomedical Named Entity Recognition](https://huggingface.co/papers/2504.00676).
+
+The code is available at [https://github.com/ds4dh/GLiNER-biomed](https://github.com/ds4dh/GLiNER-biomed).
+
 **GLiNER** is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoders (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.
 
 
@@ -107,7 +112,7 @@ We examined our models on 8 complex real-world datasets and compared them with o
 
 ### Join Our Discord
 
-Connect with our community on Discord for news, support, and discussion about our models. Join [Discord](https://discord.gg/dkyeAgs9DG).
+Connect with our community on Discord for news, support, and discussion about our models. Join [https://discord.gg/dkyeAgs9DG](https://discord.gg/dkyeAgs9DG).
 
 ## Citation