Update README.md

README.md

@@ -2,7 +2,9 @@
 license: apache-2.0
 language:
 - ar
-library_name: transformers
+tags:
+- Relation Extraction
+- Evidence Extraction
 ---
 # AREEj: Arabic Relation Extraction with Evidence
 You can use AREEj to extract relations from Arabic documents. Each document can contain multiple relations, and each relation contains six elements, the source, target, their named entities, relation type between them, and evidence. The evidence is used for two reasons: improving the Relation Extraction task, and explaining the LLM's predictions. You can also use it as an edge between the related entities.
@@ -10,7 +12,39 @@ You can use AREEj to extract relations from Arabic documents. Each document can
 AREEj was introduced in the Proceedings of The Second Arabic Natural Language Processing Conference paper [AREEj: Arabic Relation Extraction with Evidence](https://aclanthology.org/2024.arabicnlp-1.6/).
 
 
+### How to use
+```
+pip install transformers datasets evaluate transformers[torch]
+pip install sentencepiece
+```
+```python
+from transformers import MBartTokenizer, MBartForConditionalGeneration
+import torch
+
+tokenizer = MBartTokenizer.from_pretrained('dru-ac/AREEj', max_length=1024)
+model = MBartForConditionalGeneration.from_pretrained('dru-ac/AREEj')
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+
+model.to(device)
+
+def generate_prediction(input_text):
+    input_ids = tokenizer.encode(input_text, return_tensors="pt").to(device)    
+    with torch.no_grad():
+        output = model.generate(
+            input_ids,
+            decoder_start_token_id=tokenizer.lang_code_to_id['ar_AR'],
+        )
+
+    prediction = tokenizer.decode(output[0], skip_special_tokens=False)
+    
+    return prediction
+
+input_text = 'تأسس المركز العربي للأبحاث ودراسة السياسات في عام 2010 في الدوحة في قطر'
+prediction = generate_prediction(input_text)
+print('Prediction:', prediction)
+```
 
+### If you use the code or model, please reference this work in your paper:
 ```
 @inproceedings{mraikhat-etal-2024-areej,
     title = "{AREE}j: {A}rabic Relation Extraction with Evidence",