Create README.md

README.md

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+# Spider-TriviaQA: Context Encoder
+
+This is the context 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-ctx-encoder")
+model = DPRQuestionEncoder.from_pretrained("NAACL2022/spider-trivia-ctx-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)
+```