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README.md
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# Vietnam Tourism Named Entity Recognition
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We fine-tuned BERT to train Vietnam tourism dataset for a question answering system. The model was called NER2QUES because it detected tourism NER in a sentence. From that, the system generated questions corresponding to NER types.
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# How to use
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You can use the model directly
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from simpletransformers.ner import NERModel, NERArgs
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line = "King Garden is located in Thanh Thuy, Phu Tho"
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l.append(line)
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predictions, raw_outputs = model.predict(l)
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print(predictions)
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# Authors
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1. Phuc Do, University of Information Technology, Ho Chi Minh national university, Vietnam
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# Vietnam Tourism Named Entity Recognition
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We fine-tuned BERT to train Vietnam tourism dataset for a question answering system. The model was called NER2QUES because it detected tourism NER in a sentence. From that, the system generated questions corresponding to NER types.
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# How to use
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## You can use the model directly within local machine
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from simpletransformers.ner import NERModel, NERArgs
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line = "King Garden is located in Thanh Thuy, Phu Tho"
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l.append(line)
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predictions, raw_outputs = model.predict(l)
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print(predictions)
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## You can use in Transformers
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# Authors
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1. Phuc Do, University of Information Technology, Ho Chi Minh national university, Vietnam
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