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dfac358
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Parent(s):
d85b50f
Create app.py
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app.py
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from transformers import BertTokenizer, BertForSequenceClassification
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from transformers import pipeline
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import gradio as gr
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finbert = BertForSequenceClassification.from_pretrained('rpratap2102/The_Misfits', num_labels=3)
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tokenizer = BertTokenizer.from_pretrained('rpratap2102/The_Misfits')
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nlp = pipeline("sentiment-analysis", model=finbert, tokenizer=tokenizer)
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c_labels = {
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'Negative': 'This does not look good for the Market',
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'Positive': 'This seems to be good news for the market',
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'Neutral': "This is normal in the market"
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}
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def predict_sentiment(text):
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result = nlp([text])[0]
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sentiment_label = result['label']
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return c_labels[sentiment_label]
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iface = gr.Interface(
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fn=predict_sentiment,
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inputs="text",
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outputs="text",
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live=True,
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capture_session=True
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)
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iface.launch()
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