26 lines
815 B
Python
26 lines
815 B
Python
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from keybert import KeyBERT
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from transformers import AutoTokenizer, AutoModel
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# Load the SciBERT model and tokenizer
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tokenizer = AutoTokenizer.from_pretrained('allenai/scibert_scivocab_uncased')
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print("* Tokenizer")
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model = AutoModel.from_pretrained('allenai/scibert_scivocab_uncased')
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print("* Scibert model")
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# Define a KeyBERT model using SciBERT embeddings
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kw_model = KeyBERT(model=model)
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print("* Keybert model")
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# Define the subject from which to extract keywords
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subject = "tig welding of inconel 625 and influences on micro structures"
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# Extract keywords from the subject
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keywords = kw_model.extract_keywords(subject, keyphrase_ngram_range=(1, 2), stop_words='english', use_maxsum=True)
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# Print extracted keywords
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for keyword, score in keywords:
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print(f"Keyword: {keyword}, Score: {score:.4f}")
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