Dataset Viewer
Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      Dataset 'calib' has length 1000 but expected 50000
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 76, in _generate_tables
                  num_rows = _check_dataset_lengths(h5, self.info.features)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 355, in _check_dataset_lengths
                  raise ValueError(f"Dataset '{path}' has length {dset.shape[0]} but expected {num_rows}")
              ValueError: Dataset 'calib' has length 1000 but expected 50000

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

VQ-Bench Datasets: Domain-Entropy & Code Quantization Benchmarks

This repository contains high-quality, normalized HDF5 vector datasets for vector quantization benchmarking, rate-distortion curve evaluation, and multi-vector late-interaction retrieval research.

πŸ“¦ Datasets Included

File Dim Base Vectors Encoder Description / Task
colbert-python-128-normalized.hdf5 128 250,000 colbert-ir/colbertv2.0 Python source code tokens from 400 repositories with 1,000 held-out query evaluations.
colbert-rust-128-normalized.hdf5 128 250,000 colbert-ir/colbertv2.0 Rust source code tokens with static type syntax and 1,000 held-out query evaluations.
msmarco-colbert-128-normalized.hdf5 128 250,000 colbert-ir/colbertv2.0 MS MARCO general text passage token embeddings.
cifar100-clip-512-normalized.hdf5 512 50,000 openai/clip-vit-base-patch32 CIFAR-100 categorical visual embedding test set.
synthetic-shells-128.hdf5 128 50,000 Synthetic 10-layer concentric spherical shells testing non-convex manifold quantizer boundaries.

πŸ“Š HDF5 Structure

Every HDF5 file follows the standard format:

  • base: (N_base, Dim) float32 base vectors (L2-normalized).
  • calib: (N_calib, Dim) float32 calibration query vectors.
  • eval: (N_eval, Dim) float32 evaluation query vectors.
  • eval_candidates: (N_eval, 100) int32 exact brute-force top-100 neighbor indices.

πŸš€ Usage

import h5py
import numpy as np

with h5py.File("colbert-python-128-normalized.hdf5", "r") as f:
    base = f["base"][:]
    eval_q = f["eval"][:]
    gt = f["eval_candidates"][:]
    print(f"Base shape: {base.shape}, Eval shape: {eval_q.shape}")
Downloads last month
42