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            # Spider-NQ: Question Encoder
         
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            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](https://arxiv.org/abs/2112.07708).
         
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            ## Usage
         
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            We used weight sharing for the query encoder and passage encoder, so the same model should be applied for both.
         
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            **Note**! We format the passages similar to DPR, i.e. the title and the text are separated by a `[SEP]` token, but token 
         
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            type ids are all 0-s. 
         
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            An example usage:
         
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            ```python
         
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            from transformers import AutoTokenizer, DPRQuestionEncoder
         
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            tokenizer = AutoTokenizer.from_pretrained("NAACL2022/spider-trivia-question-encoder")
         
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            model = DPRQuestionEncoder.from_pretrained("NAACL2022/spider-trivia-question-encoder")
         
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            question = "Who is the villain in lord of the rings"
         
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            input_dict = tokenizer(question, return_tensors="pt")
         
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            del input_dict["token_type_ids"]
         
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            outputs = model(**input_dict)
         
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            ```
         
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