Update README/model card

README.md

@@ -9,4 +9,26 @@ app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+This space provides a gradio demo and an easy-to-run wrapper of the pre-trained model for structured sentiment analysis in Norwegian language, pre-trained on the [NoReC dataset](https://huggingface.co/datasets/norec).
+This model is an implementation of the paper "Direct parsing to sentiment graphs" (Samuel _et al._, ACL 2022). The main repository that also contains the scripts for training the model, can be found on the project [github](https://github.com/jerbarnes/direct_parsing_to_sent_graph). 
+
+The current model uses the 'labeled-edge' graph encoding, and achieves the following results on the NoReC dataset:
+
+| Unlabeled sentiment tuple F1 | Target F1  | Relative polarity precision |
+|:----------------------------:|:----------:|:---------------------------:|
+|     0.393                    |  0.468     |        0.939                |
+
+
+The model can be easily used for predicting sentiment tuples as follows: 
+
+```python
+>>> import model_wrapper
+>>> model = model_wrapper.PredictionModel()
+>>> model.predict(['vi liker svart kaffe'])
+[{'sent_id': '0',
+  'text': 'vi liker svart kaffe',
+  'opinions': [{'Source': [['vi'], ['0:2']],
+    'Target': [['svart', 'kaffe'], ['9:14', '15:20']],
+    'Polar_expression': [['liker'], ['3:8']],
+    'Polarity': 'Positive'}]}]
+```