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Runtime error
Oliver Li
commited on
Commit
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15103fe
1
Parent(s):
393a4bc
added label explanation
Browse files
app.py
CHANGED
@@ -16,15 +16,26 @@ st.write("Enter a text and select a pre-trained model to get the sentiment analy
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text = st.text_input("Enter your text:")
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# Model selection
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model_options =
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"distilbert-base-uncased-finetuned-sst-2-english"
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selected_model = st.selectbox("Choose a pre-trained model:", model_options)
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# Load the model and perform sentiment analysis
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if st.button("Analyze"):
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if not text:
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@@ -36,7 +47,7 @@ if st.button("Analyze"):
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st.write(f"Sentiment: {result[0]['label']} (confidence: {result[0]['score']:.2f})")
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if result[0]['label'] == 'POSITIVE':
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st.balloons()
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elif result[0]['label']
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st.error("Hater detected.")
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else:
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st.write("Enter a text and click 'Analyze' to perform sentiment analysis.")
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text = st.text_input("Enter your text:")
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# Model selection
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model_options = {
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"distilbert-base-uncased-finetuned-sst-2-english": {
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"labels": ["NEGATIVE", "POSITIVE"],
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"description": "This model classifies text into positive or negative sentiment. It is based on DistilBERT and fine-tuned on the Stanford Sentiment Treebank (SST-2) dataset.",
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},
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"textattack/bert-base-uncased-SST-2": {
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"labels": ["LABEL_0", "LABEL_1"],
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"description": "This model classifies text into positive(LABEL_1) or negative(LABEL_0) sentiment. It is based on BERT and fine-tuned on the Stanford Sentiment Treebank (SST-2) dataset.",
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},
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"cardiffnlp/twitter-roberta-base-sentiment": {
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"labels": ["LABEL_0", "LABEL_1", "LABEL_2"],
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"description": "This model classifies tweets into negative (LABEL_0), neutral(LABEL_1), or positive(LABEL_2) sentiment. It is based on RoBERTa and fine-tuned on a large dataset of tweets.",
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},
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}
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selected_model = st.selectbox("Choose a pre-trained model:", model_options)
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st.write("### Model Information")
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st.write(f"**Labels:** {', '.join(model_options[selected_model]['labels'])}")
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st.write(f"**Description:** {model_options[selected_model]['description']}")
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# Load the model and perform sentiment analysis
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if st.button("Analyze"):
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if not text:
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st.write(f"Sentiment: {result[0]['label']} (confidence: {result[0]['score']:.2f})")
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if result[0]['label'] == 'POSITIVE':
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st.balloons()
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elif result[0]['label'] in ['NEGATIVE', 'LABEL_0'] and result[0]['score']> 0.9:
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st.error("Hater detected.")
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else:
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st.write("Enter a text and click 'Analyze' to perform sentiment analysis.")
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