Create app.py

app.py

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+import pickle
+import gradio as gr
+from tensorflow.keras.layers import TextVectorization
+
+def sentiment_pred(text):
+    load_vectorizer = pickle.load(open("tv_layer.pkl", "rb"))
+    new_vectorizer = TextVectorization.from_config(load_vectorizer['config'])
+# You have to call `adapt` with some dummy data (BUG in Keras)
+    new_vectorizer.adapt(tf.data.Dataset.from_tensor_slices(["xyz"])) #some argues that it is not necessary 
+    new_vectorizer.set_weights(load_vectorizer['weights'])
+
+    vectorized_text = new_vectorizer([text])
+    load_model = tf.keras.models.load_model('ar_sentiment_2.h5')
+    result = load_model.predict([vectorized_text])
+    x = np.argmax(result[0])+1
+    return x 
+    
+    interface = gr.Interface(fn=sentiment_pred, 
+                         inputs=gr.inputs.Textbox(lines=2, placeholder='enter your text'),
+                         outputs=["text"])
+    interface.launch()