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Create README.md

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+
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+ from transformers import (
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+ AutoModelForSequenceClassification,
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+ AutoTokenizer,
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+ )
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+
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+ model = AutoModelForSequenceClassification.from_pretrained("shahrukhx01/roberta-base-boolq")
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+ model.to(device)
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+ #model.push_to_hub("roberta-base-boolq")
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+
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+ tokenizer = AutoTokenizer.from_pretrained("shahrukhx01/roberta-base-boolq")
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+
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+ def predict(question, passage):
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+ sequence = tokenizer.encode_plus(question, passage, return_tensors="pt")['input_ids'].to(device)
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+
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+ logits = model(sequence)[0]
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+ probabilities = torch.softmax(logits, dim=1).detach().cpu().tolist()[0]
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+ proba_yes = round(probabilities[1], 2)
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+ proba_no = round(probabilities[0], 2)
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+
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+ print(f"Question: {question}, Yes: {proba_yes}, No: {proba_no}")
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+
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+ passage = """Berlin is the capital and largest city of Germany by both area and population. Its 3.8 million inhabitants make it the European Union's most populous city,
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+ according to population within city limits."""
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+
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+ question = "Is Berlin the smallest city of Germany?"
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+ predict(s_question, passage)