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