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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MS MARCO ColBERT Embeddings

Pre-computed ColBERT embeddings for MS MARCO using PyLate and answerdotai/answerai-colbert-small-v1.

Dataset Structure

The dataset contains:

data/corpus/: 177 parquet files with document embeddings
data/queries/: 11 parquet files with query embeddings
data/qrels/train.parquet: Relevance judgments (532,751 pairs)

Usage

from datasets import load_dataset

# Load from directory (recommended for large datasets)
corpus = load_dataset("parquet", data_dir="hf://datasets/WenxingZhu/msmarco_answerai_colbert_small_embeddings/data/corpus")
queries = load_dataset("parquet", data_dir="hf://datasets/WenxingZhu/msmarco_answerai_colbert_small_embeddings/data/queries")
qrels = load_dataset("parquet", data_files="hf://datasets/WenxingZhu/msmarco_answerai_colbert_small_embeddings/data/qrels/train.parquet")

Model

Generated with answerdotai/answerai-colbert-small-v1

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Total file size:

364 GB