Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/arrow/arrow.py", line 45, in _split_generators
                  self.info.features = datasets.Features.from_arrow_schema(reader.schema)
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1971, in from_arrow_schema
                  metadata_features = Features.from_dict(metadata["info"]["features"])
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2009, in from_dict
                  obj = generate_from_dict(dic)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1588, in generate_from_dict
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                               ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1597, in generate_from_dict
                  feature = obj.pop("feature")
              KeyError: 'feature'
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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.

CellxGene + scBaseCount, human, tokenized

Geneformer-style rank-value tokenized human cells: a straightforward union of two existing public corpora, CellxGene Discover (cxg_raw_2025-11-08) and scBaseCount (2025-02-25), deduplicated (CellxGene's own is_primary_data flag, to drop repeated cells across dataset views) and tokenized. 211,221,738 cells. This is not an original data-collection effort -- all underlying cells were already public via CellxGene Discover and scBaseCount; this repo is just that union in a ready-to-train tokenized form.

Contents

  • Repo root -- a HuggingFace datasets DatasetDict (single train split) saved via save_to_disk (dataset_dict.json, train/). Columns: input_ids (large_list, Geneformer-style rank-value encoding, <cls>-prefixed, truncated to 4096 tokens), cell_index, length, species (always "hsapiens" here).
  • vocab/hsapiens_token_dictionary.pkl -- the exact vocab these ids were tokenized against (23,266 genes + special tokens: <pad>=0, <mask>=1, <cls>=2, <eos>=3, genes 4..). This is not the same as the default packaged token_dictionary.pkl (~20k genes) -- loading with the wrong vocab silently misaligns gene ids.
  • vocab/hsapiens_gene_medians.pkl -- non-zero median gene expression values used by the tokenizer's normalization step, computed from this same corpus/vocab.

Loading

from huggingface_hub import snapshot_download
from datasets import load_from_disk

local_dir = snapshot_download(repo_id="theislab/cellxgene-scbasecount-human-tokenized", repo_type="dataset")
ds = load_from_disk(local_dir)["train"]
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