khandelwalkishna15
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40c7739
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new update
Browse files- sentiment_analysis.py +0 -17
sentiment_analysis.py
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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# Load pre-trained model and tokenizer
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#model_name = "ProsusAI/finbert"
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#model_name = "ahmedrachid/FinancialBERT-Sentiment-Analysis"
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model_name="mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSequenceClassification.from_pretrained(model_name)
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# Example: Classify a financial text
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text = "With the launch of Apple Silicon, Apple shares have increased"
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inputs = tokenizer(text, return_tensors="pt")
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outputs = model(**inputs)
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predictions = outputs.logits.argmax(dim=1).item()
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# 'predictions' will contain the sentiment class (e.g., 0 for negative, 1 for neutral, 2 for positive)
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print("Predicted sentiment class:", predictions)
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