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--- |
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language: "en" |
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tags: |
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- dstc10 |
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- knowledge title-body validation |
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widget: |
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- text: "Can you accommodate large groups? It does not offer free WiFi." |
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- text: "Is there a gym on site? It does not have an onsite fitness center." |
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--- |
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This is the model used for knowledge clustering where we feed title-body pair and the classifier predicts if the pair is valid or not. |
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For further information, please refer to https://github.com/yctam/dstc10_track2_task2 for the Github repository. |
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Credit: Jiakai Zou, Wilson Tam |
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--- |
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```python |
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from transformers import AutoConfig, AutoTokenizer, AutoModelForSequenceClassification |
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def single_test(tokenizer, title_body_pair): |
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result = tokenizer([title_body_pair], return_tensors="pt") |
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model.eval() |
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outputs = model(**result) |
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predictions = outputs.logits.argmax(dim=-1) |
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# There was a mistake in flipping the labels. |
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return True if predictions == 0 else False |
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if __name__ == '__main__': |
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model_name = "wilsontam/bert-base-uncased-dstc10-kb-title-body-validate" |
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config = AutoConfig.from_pretrained(model_name) |
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tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True) |
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model = AutoModelForSequenceClassification.from_pretrained(".") |
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sentence = "Can I check in anytime?" |
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body = "Yes, 24 Hours Front Desk Avaliable." |
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print(single_test((sentence, body))) # Expect: True |
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``` |
