Update app.py

app.py

@@ -22,9 +22,9 @@ model = AutoModelForSequenceClassification.from_pretrained("paragon-analytics/AD
 pred = transformers.pipeline("text-classification", model=model, 
                              tokenizer=tokenizer, return_all_scores=True)
 
+explainer = shap.Explainer(pred)
 
 def interpretation_function(text):
-    explainer = shap.Explainer(pred)
     shap_values = explainer([text])
     scores = list(zip(shap_values.data[0], shap_values.values[0, :, 1]))
     return scores
@@ -46,7 +46,7 @@ def interpretation_function(text):
 #     return val
 
 def adr_predict(x):
-    encoded_input = tokenizer(x, return_tensors='pt')
+    encoded_input = tokenizer(str(x), return_tensors='pt')
     output = model(**encoded_input)
     scores = output[0][0].detach().numpy()
     scores = tf.nn.softmax(scores)
@@ -93,7 +93,6 @@ def adr_predict(x):
     # , word_attributions ,scores
 
 def main(text):
-    text = str(text).lower()
     obj = adr_predict(text)
     return obj[0],obj[1]
     # ,obj[2]