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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/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Column(/estimated_value_min) changed from number to string in row 201
              
              During handling of the above exception, another exception occurred:
              
              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/json/json.py", line 101, in _split_generators
                  pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
                             ~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
                  batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
                  examples = [ujson_loads(line) for line in original_batch.splitlines()]
                              ~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
                  return pd.io.json.ujson_loads(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
              ValueError: Value is too big!
              
              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.

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US Government Bids — Historical Sample

10,000 historical US government procurement bids with full titles, descriptions, and structured metadata. All bids in this dataset have due dates at least 30 days in the past — this is a historical corpus for research and ML training, not a live opportunity feed.

Source: ProcureTap — aggregated from 290+ federal, state, and local procurement portals (SAM.gov, Grants.gov, state portals, Bonfire, PlanetBids, Jaggaer, BidNet Direct, DemandStar, and many more).

License: CC-BY-4.0. Free to redistribute with attribution.

Refresh cadence: Monthly.

Citation:

ProcureTap (2026). US Government Bids — Historical Sample. https://huggingface.co/datasets/ProcureTap/us-government-bids-sample

Schema

Each line in bids.jsonl is a JSON object with the following fields:

Field Type Description
id int ProcureTap internal ID (stable, referenceable at procuretap.com/bid/{id})
external_id string | null Original solicitation number from the source system
title string Bid title (as scraped from source, may include prefixes/codes)
description string Bid description text (truncated to 2,500 characters where longer)
state string | null 2-letter US state code (federal bids may be null or "US")
city string | null City if location-specific
industry string | null Industry classification (comma-separated for multi-industry)
bid_type string | null RFP / RFQ / IFB / ITB / etc.
status string closed / awarded / open (open here means due_date past but source system hasn't marked closed yet)
posted_date string (ISO 8601) | null Date bid was posted by the agency
due_date string (ISO 8601) Deadline for responses (always >30 days in the past for this dataset)
award_date string (ISO 8601) | null If awarded, the date of award
estimated_value_min number | null Lower bound of contract value in USD (where disclosed)
estimated_value_max number | null Upper bound of contract value in USD (where disclosed)
source_url string | null URL to the original source posting
source_platform string | null The originating platform (e.g., sam_gov, bonfire, planetbids)
org_name string | null Name of the issuing agency/organization
org_type string | null Agency type (federal, state, city, county, school_district, hospital, university, etc.)
org_state string | null The state where the organization is based

What is EXCLUDED

To protect privacy and honor the terms of aggregation from source systems:

  • Contact information (name, email, phone) is stripped from every record
  • Full RFP document text is not included (only the bid metadata + description)
  • No bids with due_date less than 30 days ago (protects the value of live procurement data)
  • No bids with descriptions shorter than 100 characters (low signal)
  • No bids with titles shorter than 10 characters (usually stubs or errors)

Suggested uses

  • Text classification: train models to classify RFPs by industry, agency type, or contract type
  • Named-entity recognition: extract dollar amounts, deadline dates, set-aside categories, geographic locations
  • Summarization: generate short summaries of long procurement descriptions
  • Question answering: answer questions about historical government procurement patterns
  • Embedding models: build vector representations of procurement documents for similarity search
  • Baseline data: benchmark procurement-aware AI assistants against real-world procurement text

Related dataset

For aggregate statistics (bid counts by state, industry, agency, total value), see ProcureTap/us-government-procurement-stats.

About ProcureTap

ProcureTap is a US government procurement bid aggregation platform. Free tier lets anyone browse and search 200,000+ active government contracts across federal, state, and local agencies. Pro tier ($99/mo) adds instant email alerts, unlimited saved searches, and full document access. The live data on procuretap.com is refreshed every 6 hours.

If this dataset is useful to your work, attribution back to procuretap.com is appreciated (though not legally required beyond CC-BY-4.0 terms).

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