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aded distilbert interface
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app.py
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import gradio as gr
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from
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preds = model.predict([text])
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iface.
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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 with DistilBERT
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distilbert_pipeline = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
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def predict_sentiment(text):
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"""
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Predicts the sentiment of the input text using DistilBERT.
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:param text: str, input text to analyze.
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:return: str, predicted sentiment and confidence score.
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"""
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result = distilbert_pipeline(text)[0]
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label = result['label']
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score = result['score']
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return f"Sentiment: {label}, Confidence: {score:.2f}"
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# Create a Gradio interface
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iface = gr.Interface(fn=predict_sentiment,
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inputs=gr.inputs.Textbox(lines=2, placeholder="Type your text here..."),
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outputs="text",
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title="Sentiment Analysis with DistilBERT",
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description="This model predicts the sentiment of the input text. Enter a sentence to see if it's positive or negative.")
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# Launch the interface
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iface.launch()
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