Update app.py

app.py

@@ -25,9 +25,10 @@ pred = transformers.pipeline("text-classification", model=model,
 
 explainer = shap.Explainer(pred)
 
-tokenizer = AutoTokenizer.from_pretrained("Clinical-AI-Apollo/Medical-NER")
-model = AutoModelForTokenClassification.from_pretrained("Clinical-AI-Apollo/Medical-NER")
-ner_pipe = pipeline("ner", model=ner_model, tokenizer=ner_tokenizer, aggregation_strategy="simple")
+ner_tokenizer = AutoTokenizer.from_pretrained("Clinical-AI-Apollo/Medical-NER")
+ner_model = AutoModelForTokenClassification.from_pretrained("Clinical-AI-Apollo/Medical-NER")
+
+ner_pipe = pipeline("ner", model=ner_model, tokenizer=ner_tokenizer, aggregation_strategy="simple") # pass device=0 if using gpu
 
 def adr_predict(x):
     encoded_input = tokenizer(x, return_tensors='pt')