Update README.md

README.md

@@ -49,12 +49,29 @@ BioBERT based NER model for medical symptoms
 
 
 
-The model was trained on the combined maccrobat and i2c2 dataset and is based on biobert. If you use the model kindly cite the paper below:
+<em> Model Description </em>
+
+The model was trained on a combined maccrobat and i2c2 dataset and is based on biobert. If you use this model kindly cite the paper below:
 
 <em>
 <b>Developing a BioBERT-based Natural Language Processing Algorithm for Acute Myeloid Leukemia Symptoms Identification from Clinical Notes - Sena Chae , Pratik Maitra , Padmini Srinivasan</b>
 </em>
 
+<em> How to use the Model </em>
+
+<div class="wrapper">
+    <span class="inner">
+
+from transformers import pipeline, AutoTokenizer, AutoModelForTokenClassification
+
+tokenizer = AutoTokenizer.from_pretrained("d4data/biomedical-ner-all")
+model = AutoModelForTokenClassification.from_pretrained("d4data/biomedical-ner-all")
+
+pipe = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="simple") # pass device=0 if using gpu
+pipe("""The patient reported no recurrence of palpitations at follow-up 6 months after the ablation.""")
+
+</span>
+</div>
 ### Accuracy
 
 | Type | Score |