| import streamlit as st | |
| from transformers import pipeline | |
| def sentiment_funtion(text): | |
| model = pipeline("sentiment-analysis", model="stevhliu/my_awesome_model") | |
| output = model(text)[0] | |
| label = output["label"] | |
| score = output["score"] | |
| return label , score | |
| def main(): | |
| st.title("Dineth") | |
| st.sidebar.image("https://huggingface.co/spaces/Dineth98/TA_1/resolve/main/sentiment-analysis-1280x720.jpg", use_column_width=True) | |
| st.sidebar.subheader("About This App") | |
| st.sidebar.write("Fuck off") | |
| user_input = st.text_area("Input Text Here") | |
| if st.button("Sentiment"): | |
| label , score = sentiment_funtion(user_input) | |
| if label == "LABEL_1": | |
| label = "Positive" | |
| postive_score = score | |
| negative_score = 1 - score | |
| color = "green" | |
| else: | |
| label = "Negative" | |
| postive_score = 1 - score | |
| negative_score = score | |
| color = "red" | |
| style = f'color:{color}' | |
| text = f'Sentiment Label: {label}' | |
| sentiment_text = f'<h4 style="{style}">{text}</h4>' | |
| st.write("Sentiment:") | |
| st.write(sentiment_text, unsafe_allow_html=True) | |
| st.write(f"Positive Score: {postive_score:.2f}") | |
| st.write(f"Negative Score: {negative_score:.2f}") | |
| if __name__ == "__main__": | |
| main() |