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| import streamlit as st | |
| from transformers import pipeline, AutoTokenizer | |
| model_path = "citizenlab/twitter-xlm-roberta-base-sentiment-finetunned" | |
| sentiment_classifier = pipeline("text-classification", model=model_path, tokenizer=model_path) | |
| model_name = "citizenlab/twitter-xlm-roberta-base-sentiment-finetunned" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| def main(): | |
| st.title("Twitter Sentiment Analysis") | |
| with st.form("text_field"): | |
| text = st.text_area('Enter some text:') | |
| # clicked == True เมื่อปุ่มถูกคลิก | |
| clicked = st.form_submit_button("Analyze Sentiment") | |
| if clicked: | |
| # วิเคราะห์ความรู้สึกของข้อความ | |
| results = sentiment_classifier(text) | |
| st.write("Sentiment Analysis Results:") | |
| for result in results: | |
| st.write(f"Label: {result['label']}, Score: {result['score']:.4f}") | |
| if __name__ == "__main__": | |
| main() |