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Browse files- app.py +22 -0
- requirements.txt +3 -0
app.py
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import gradio as gr
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from transformers import pipeline
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# Load the sentiment analysis pipeline
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sentiment_pipeline = pipeline("sentiment-analysis")
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# Define the function that will use the model
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def analyze_sentiment(text):
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result = sentiment_pipeline(text)[0]
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return {"label": result['label'], "score": result['score']}
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# Create the Gradio interface
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iface = gr.Interface(
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fn=analyze_sentiment,
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inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
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outputs="json",
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title="Sentiment Analysis",
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description="A simple sentiment analysis web app using Hugging Face Transformers."
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)
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if __name__ == "__main__":
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iface.launch()
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requirements.txt
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transformers
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torch
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gradio
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