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app.py

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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()

requirements.txt

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+torch
+transformers
+altair<5