OpenWebText English Web Corpus
Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- cc0-1.0
- Source / creator
- Skylion007/openwebtext
- Collection method
- The creators replicated OpenAI's WebText collection methodology: scrape all outbound URLs posted to Reddit submissions with at least 3 karma, deduplicate, filter out non-English and low-quality content, and extract main article text using Newspaper. The output approximates the distribution and content of the original (unreleased) WebText corpus used by OpenAI for GPT-2 training.
- Coverage start
- Not documented
- Coverage end
- Not documented
- Data last updated
- Not documented
- Update schedule
- Not documented
- Heavily English-monolingual; non-English content was filtered out. - Reddit-sourced URL selection introduces demographic and topical biases (over-representation of tech, US politics, popular-culture subreddits popular ~2018). - No safety/toxicity filtering; corpus contains profanity, NSFW content, and offensive material consistent with the open web. - Time-frozen snapshot reflecting links shared on Reddit prior to ~2019; no ongoing updates. - Known overlap risk with common LM evaluation benchmarks — leakage must be checked before using for eval-adjacent training. - Deduplication is approximate; near-duplicates exist across documents.
Sample structure score: 100 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (JSON) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 50 / 50 | 10 of 10 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 10 of 10 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| text | 0 / 10 | string | 0 / 10 |
About this data
Open-source replication of OpenAI's WebText corpus used for GPT-2 pretraining. Contains approximately 8 million English web documents suitable for language model training and research.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py d2f7287a-dfd1-460b-9330-be8efd5f85ba --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| text | VARCHAR | Full plain-text content of a web document scraped from Reddit-shared URLs |
Sample Data
Preview a sample of the data before downloading.
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For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "OpenWebText English Web Corpus" })
// Found: d2f7287a-dfd1-460b-9330-be8efd5f85ba
get_download_url({ dataset_id: "d2f7287a-dfd1-460b-9330-be8efd5f85ba" }) // free — sign in with MCP OAuth first# Free dataset — sign in or use your account API key: curl https://api.databazaar.io/datasets/d2f7287a-dfd1-460b-9330-be8efd5f85ba/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"