Update app.py

app.py

@@ -57,19 +57,14 @@ classificationResult = pipe("El objetivo de esta tesis es elaborar un estudio de
 
 
 def thesis_prediction(input):
-              tokenizer = AutoTokenizer.from_pretrained('"hiiamsid/BETO_es_binary_classification"', use_fast=False)             
+    tokenizer = AutoTokenizer.from_pretrained('"hiiamsid/BETO_es_binary_classification"', use_fast=False)             
 
-              model = AutoModelForSequenceClassification.from_pretrained(
-                   'hackathon-pln-es/unam_tesis_BETO_finnetuning', num_labels=5, output_attentions=False,
-                  output_hidden_states=False)
-            
-              pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True)
-              classificationResult = pipe(input)
-              classificationResult[0].sort(reverse=True, key=lambda x:x['score'])
-              keyClass = classificationResult[0][0]['label']
-              #     # Return the text clasification
-              #     keyClass = classificationResult[0][0]['label']
-              return keyClass
+    model = AutoModelForSequenceClassification.from_pretrained('hackathon-pln-es/unam_tesis_BETO_finnetuning', num_labels=5, output_attentions=False, output_hidden_states=False)
+    pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True)
+    classificationResult = pipe(input)
+    classificationResult[0].sort(reverse=True, key=lambda x:x['score'])
+    keyClass = classificationResult[0][0]['label']
+    return keyClass
               
 
 examples = [