Update app.py

app.py

@@ -1,48 +1,48 @@
 # import sentencepiece
 
 
-import streamlit as st
-from transformers import pipeline
+# import streamlit as st
+# from transformers import pipeline
 
-sentiment_analysis = pipeline("sentiment-analysis")
-translation = pipeline("translation_en_to_ar", model="anibahug/marian-finetuned-kde4-en-to-ar")
+# sentiment_analysis = pipeline("sentiment-analysis")
+# translation = pipeline("translation_en_to_ar", model="anibahug/marian-finetuned-kde4-en-to-ar")
 
-text = st.text_input("Enter some text")
+# text = st.text_input("Enter some text")
 
-if text:
-    result = sentiment_analysis(text)
-    st.json(result)
+# if text:
+#     result = sentiment_analysis(text)
+#     st.json(result)
 
-if text:
-    result = translation(text)[0]
-    st.write(f"Translated text: {result['translation_text']}")
+# if text:
+#     result = translation(text)[0]
+#     st.write(f"Translated text: {result['translation_text']}")
 
 
 
 
 
-# import streamlit as st
-# from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer
+import streamlit as st
+from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer
 
-# # Load sentiment analysis model from Hugging Face
-# model_name = "distilbert-base-uncased-finetuned-sst-2-english"
-# model = AutoModelForSequenceClassification.from_pretrained(model_name)
-# tokenizer = AutoTokenizer.from_pretrained(model_name)
-# sentiment_analyzer = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
+# Load sentiment analysis model from Hugging Face
+model_name = "distilbert-base-uncased-finetuned-sst-2-english"
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+sentiment_analyzer = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
 
-# # Streamlit UI
-# st.title("Sentiment Analysis App")
+# Streamlit UI
+st.title("Sentiment Analysis App")
 
-# # User input
-# user_input = st.text_input("Enter a sentence:")
+# User input
+user_input = st.text_input("Enter a sentence:")
 
-# if user_input:
-#     # Perform sentiment analysis
-#     results = sentiment_analyzer(user_input)
+if user_input:
+    # Perform sentiment analysis
+    results = sentiment_analyzer(user_input)
     
-#     # Display sentiment and confidence
-#     sentiment = results[0]['label']
-#     confidence = results[0]['score']
+    # Display sentiment and confidence
+    sentiment = results[0]['label']
+    confidence = results[0]['score']
     
-#     st.write(f"Sentiment: {sentiment}")
-#     st.write(f"Confidence: {confidence:.2f}")
+    st.write(f"Sentiment: {sentiment}")
+    st.write(f"Confidence: {confidence:.2f}")