Datasets:

astr010
/

sec-10k-markdown-compressed

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/webdataset/webdataset.py", line 81, in _split_generators
                  first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
                  fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
                                                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
                  cls = get_filesystem_class(protocol)
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
                  raise ValueError(f"Protocol not known: {protocol}")
              ValueError: Protocol not known: memory
              
              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 71, 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.

📦 SEC 10-K Full Markdown Filings (Compressed Archives)

Dataset Summary

This dataset contains 12,361 full-length SEC Form 10-K annual reports converted from EDGAR HTML to clean Markdown format across 1,379 companies (spanning 2004 to 2025, core 2014–2025).

The filings are packaged as 1,379 compressed .tar.gz archives (1 archive per company ticker). Each archive contains the un-chunked annual 10-K Markdown reports and a JSON metadata manifest (manifest.json).

📊 Dataset Statistics

Metric	Value
Total Companies (Tickers)	1,379 companies
Total 10-K Filings	12,361 full-length `.md` documents
File Format	Compressed `.tar.gz` archives (1 per ticker)
Compressed Dataset Size	1.18 GB
Uncompressed Dataset Size	4.75 GB
Fiscal Years Covered	2004 – 2025 (Core: 2014–2025)
Primary Language	English
Licensing	MIT

📄 Archive Structure

Each .tar.gz archive is named {TICKER}_filings.tar.gz (e.g. AAPL_filings.tar.gz, NVDA_filings.tar.gz, MSFT_filings.tar.gz) and contains:

{TICKER}_filings.tar.gz/
└── {TICKER}/
    ├── 10-K_2014.md
    ├── 10-K_2015.md
    ├── ...
    ├── 10-K_2024.md
    └── manifest.json

💻 Extracting & Using in Python

import tarfile, os
from huggingface_hub import hf_hub_download

# Download a specific ticker archive
file_path = hf_hub_download(
    repo_id="astr010/sec-10k-markdown-compressed",
    filename="AAPL_filings.tar.gz",
    repo_type="dataset"
)

# Extract and read filings
with tarfile.open(file_path, "r:gz") as tar:
    for member in tar.getmembers():
        if member.name.endswith(".md"):
            f = tar.extractfile(member)
            content = f.read().decode("utf-8")
            print(f"Read {member.name} ({len(content):,} chars)")

📜 Licensing & Citation

This dataset is released under the MIT License.

@dataset{sec_10k_markdown_compressed_2026,
  author       = {Tim Condello},
  title        = {SEC 10-K Full Markdown Filings (Compressed Archives)},
  year         = {2026},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/astr010/sec-10k-markdown-compressed}}
}

Downloads last month: 50

Total file size:

1.28 GB