Diya-Roshan/code-mixed-text-sentiment-classification

1import streamlit as st2from simpletransformers.classification import MultiLabelClassificationModel3import torch4 5# Function to make predictions6def predict(model, text):7    raw_outputs, _ = model.predict([text])8    return raw_outputs9 10# Streamlit App11def main():12    st.title("Dravidian-English Code Mixed TextSentiment Prediction App")13 14    # Language model selection15    selected_language = st.selectbox("Select Language Model", ["Kannada", "Malayalam", "Tamil"])16 17    # Load the pre-trained model based on the selected language18    model_paths = {19        "Kannada": "Diya-Roshan/xlm-code-mixed-kannada-sentiment-classifier",20        "Malayalam": "Diya-Roshan/xlm-code-mixed-malayalam-sentiment-classifier",  21        "Tamil": "Diya-Roshan/xlm-code-mixed-tamil-sentiment-classifier",  22    }23 24    if selected_language in model_paths:25        model_path = model_paths[selected_language]26        model = MultiLabelClassificationModel('xlm', model_path, use_cuda=False)27 28        # User input for text29        text_input = st.text_area("Enter text for prediction", "")30 31        # Make predictions when the user clicks the button32        if st.button("Predict"):33            if text_input:34                predictions = predict(model, text_input)35 36                # Display the predictions37                if predictions == [[1, 0, 0]]:38                    st.success('Positive Sentiment')39                elif predictions == [[0, 1, 0]]:40                    st.error('Negative Sentiment')41                else:42                    st.warning('Mixed Sentiment')43 44if __name__ == "__main__":45    main()46