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# Spider-TriviaQA: Question Encoder
This is the question encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper [Learning to Retrieve Passages without Supervision](https://arxiv.org/abs/2112.07708).
## 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:
```python
from transformers import AutoTokenizer, DPRQuestionEncoder
tokenizer = AutoTokenizer.from_pretrained("NAACL2022/spider-trivia-question-encoder")
model = DPRQuestionEncoder.from_pretrained("NAACL2022/spider-trivia-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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