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Spider-NQ: Question Encoder
This is the question encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.
Usage
We used weight sharing for the query encoder and passage encoder, so the same model should be applied for both.
Note! We format the passages similar to DPR, i.e. the title and the text are separated by a [SEP] token, but token
type ids are all 0-s.
An example usage:
from transformers import AutoTokenizer, DPRQuestionEncoder
tokenizer = AutoTokenizer.from_pretrained("NAACL2022/spider-nq-question-encoder")
model = DPRQuestionEncoder.from_pretrained("NAACL2022/spider-nq-question-encoder")
question = "Who is the villain in lord of the rings"
input_dict = tokenizer(question, return_tensors="pt")
del input_dict["token_type_ids"]
outputs = model(**input_dict)
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