Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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Wiki-DPR (first 10k samples of the "multiset" version)

Overview

This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model. The original dataset contains 21M passages from wikipedia along with their DPR embeddings. The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.

Embeddings

Passages are embedded using this model: https://huggingface.co/sentence-transformers/facebook-dpr-ctx_encoder-multiset-base

Questions should embedded using this model: https://huggingface.co/sentence-transformers/facebook-dpr-question_encoder-multiset-base

Dataset format

The dataset is in Lance format and contains an index over the embeddings column, created using

>>> table.create_index(metric="dot", vector_column_name="embeddings")

Usage example

>>> import lance
>>> from sentence_transformers import SentenceTransformer
>>> ds = lance.dataset("hf://datasets/lhoestq/wiki-dpr-lance-example/dummy-multiset.lance")
>>> ds.has_index
True
>>> q = embeddings = model.encode(["In what year did ABBA start ?"])[0]
>>> df = ds.to_table(nearest={"column": "embeddings", "q": embeddings, "k": 5}).to_pandas()
>>> df
                                          embeddings    id                                               text title  _distance
0  [-0.18065824, 0.25305566, 0.1199052, -0.571353...  9929  numbers from respective albums, but the lukewa...  ABBA -71.944893
1  [-0.40663224, 0.22715698, 0.06069667, -0.33584...  9934  small label like Playboy Records did not have ...  ABBA -71.606918
2  [-0.11441193, -0.08622038, 0.1414486, -0.53792...  9931  into the mainstream international market with ...  ABBA -71.264702
3  [-0.10480262, 0.24277505, 0.0049878294, -0.406...  9930  on her own. Frequent recording sessions brough...  ABBA -71.059311
4  [-0.013585132, 0.010848946, 0.29921767, -0.283...  9933  credited to  Björn & Benny, Agnetha & Anni-Fri...  ABBA -71.030861
>>> df.iloc[0].text[435:544]
"It was during 1971 that the four artists began working together more, adding vocals to the others' recordings"

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