| import gradio as gr | |
| import tensorflow as tf | |
| # Load the saved model | |
| model = tf.keras.models.load_model("sentimentality.h5") | |
| def predict_sentiment(text): | |
| # preprocess input text | |
| processed_text = preprocess(text) | |
| # predict sentiment | |
| prediction = model.predict([processed_text])[0][0] | |
| sentiment = 'positive' if prediction >= 0.5 else 'negative' | |
| return sentiment | |
| iface = gr.Interface(fn=predict_sentiment, | |
| inputs=gr.inputs.Textbox(label='Input Text'), | |
| outputs=gr.outputs.Label(label='Sentiment Prediction')) | |
| iface.launch() |