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Update README.md

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  # DistilBERT IMDB Sentiment Classifier
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  ## Overview
@@ -40,4 +59,4 @@ inputs = tokenizer("This movie was excellent!", return_tensors="pt")
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  outputs = model(**inputs)
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  prediction = torch.argmax(outputs.logits).item()
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- print("Positive" if prediction == 1 else "Negative")
 
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+ ---
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+ language: en
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+ license: mit
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+ datasets:
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+ - imdb
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+ metrics:
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+ - accuracy
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+ - f1
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+ pipeline_tag: text-classification
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+ base_model: distilbert/distilbert-base-uncased
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+ library_name: transformers
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+ tags:
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+ - fine-tune-model
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+ - sentiment-analysis
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+ - distilbert
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+ - text-classification
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+ - imdb
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+ ---
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+
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  # DistilBERT IMDB Sentiment Classifier
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  ## Overview
 
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  outputs = model(**inputs)
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  prediction = torch.argmax(outputs.logits).item()
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+ print("Positive" if prediction == 1 else "Negative")