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app.py

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+
+import gradio as gr
+import numpy as np
+
+#loading the saved model 
+from keras.models import load_model 
+model = load_model('model.h5')
+
+import gradio as gr
+
+def page(word):
+  word_tk= tokenizer.texts_to_sequences([word])
+
+  word_pad= pad_sequences(word_tk, maxlen=10)
+  prediction = model.predict(word_pad)
+  f_prediction= np.argmax(prediction)
+  if f_prediction == 1:
+   return "Authentic"
+  elif f_prediction ==2:
+   return "Normal"
+  elif f_prediction ==3:
+   return "Not Authentic"
+  else:
+   return "Error"
+  s
+
+demo = gr.Interface(
+    fn=page,
+    inputs=gr.Textbox(placeholder="Enter your review and the rating to check the authenticity of any product or page"),
+    outputs="text",
+)
+
+demo.launch()