Update app.py

app.py

@@ -3,6 +3,7 @@ from huggingface_hub import from_pretrained_keras
 from huggingface_hub import KerasModelHubMixin
 import transformers
 from transformers import AutoTokenizer
+import numpy as np
 
 
 m = from_pretrained_keras('sgonzalezsilot/FakeNews-Detection-Twitter-Thesis')
@@ -41,8 +42,16 @@ def bert_encode(tokenizer,data,maximum_length) :
 def get_news(input_text):
   sentence_length = 110
   train_input_ids,train_attention_masks = bert_encode(tokenizer,input_text,sentence_length)
-    
-  return m([train_input_ids,train_attention_masks])
+
+  pred = m.predict([train_input_ids,train_attention_masks])
+  pred = np.round(pred)
+  pred = pred.flatten()
+
+  if pred == 1:
+      result = "Fake News"
+  else:
+      result = "True News"
+  return result
 
 iface = gr.Interface(fn = get_news, 
                      inputs = "text",