Update README.md

README.md

@@ -17,18 +17,17 @@ This model is a fine-tuned version of [DeBERTa](https://huggingface.co/microsoft
 
 ## Model description
 
-This model is trained to serve the RaTEScore metric, if you are interested in our pipeline, please refer to our [paper](https://angelakeke.github.io/RaTEScore/).
+This model is trained to serve the RaTEScore metric, if you are interested in our pipeline, please refer to our [paper](https://angelakeke.github.io/RaTEScore/) and [Github](https://github.com/Angelakeke/RaTEScore).
 
 This model also can be used to extract  **Abnormality, Non-Abnormality, Anatomy, Disease, Non-Disease**
 in medical radiology reports.
 
 ## Usage
 ```python
-# Load model directly
 from transformers import AutoTokenizer, AutoModelForTokenClassification
 
-tokenizer = AutoTokenizer.from_pretrained("Angelakeke/RaTE-NER")
-model = AutoModelForTokenClassification.from_pretrained("Angelakeke/RaTE-NER")
+tokenizer = AutoTokenizer.from_pretrained("Angelakeke/RaTE-NER-Deberta")
+model = AutoModelForTokenClassification.from_pretrained("Angelakeke/RaTE-NER-Deberta")
 ```
 
 ## Author