Update README.md

README.md

@@ -1,3 +1,43 @@
----
-license: mit
----
+---
+license: mit
+language:
+- en
+tags:
+- medical
+- radiology
+model-index:
+- name: rate-ner-rad
+  results: []
+pipeline_tag: token-classification
+---
+
+# rate-ner-rad
+
+This model is a fine-tuned version of [DeBERTa](https://huggingface.co/microsoft/deberta-v3-base) on the [RaTE-NER]() dataset.
+
+## 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 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")
+```
+
+## Author
+
+Author: [Weike Zhao](https://angelakeke.github.io/)
+
+If you have any questions, please feel free to contact [email protected].
+
+## Citation
+```
+
+```