Download templates/dataset-card-template.md from KrazyKitty/Data-Lab: direct link, hf CLI and curl.
- Browser
- Download file 2.55 kB
-
https://huggingface.co/datasets/KrazyKitty/Data-Lab/resolve/main/templates/dataset-card-template.md
- Command line
-
hf download hf://datasets/KrazyKitty/Data-Lab/templates/dataset-card-template.md
-
curl -L -o dataset-card-template.md https://huggingface.co/datasets/KrazyKitty/Data-Lab/resolve/main/templates/dataset-card-template.md
license: <reviewed-spdx-identifier-or-other>
pretty_name: <dataset-display-name>
language:
- <language-tag>
tags:
- <purpose-tag>
Dataset Card for <dataset-id>
Template only. Replace every angle-bracket field and remove this notice before release.
Summary
- Version:
<immutable-version> - Status:
<proposed | approved-for-private-research | released | withdrawn> - Maintainer:
<responsible-owner> - Canonical source manifest:
<path-or-immutable-link-and-sha256> - Release decision:
<approval-record>
Describe what the dataset contains and what evidence supports that description. Do not promote a planned collection or processing pipeline into a released dataset claim.
Intended uses
Supported
<specific, evidence-backed research use>
Out of scope
<use not evaluated or not permitted>
Source data and provenance
For every source, provide the publisher, canonical URL, version/revision, retrieval date, integrity digest, licence, permission scope, privacy review, consent or lawful basis, and transformation lineage. Link to a machine-readable manifest without exposing private paths or source content.
Processing
Record the exact code revision, configuration, command, dependency lock, input/output hashes, filter versions, exclusion counts, deduplication method, and split assignment.
Composition and splits
Report records, bytes, characters, tokens (with tokenizer version), languages, domains, time range, formats, source mixture, missing values, duplicates, and rejection counts for every split.
Licensing, privacy, and consent
Explain the licence analysis, attribution, redistribution rights, privacy controls, sensitive-data review, consent or other lawful basis, retention, withdrawal, and deletion process.
Quality and validation
Provide scoped measurements, manual-review sampling, contamination checks, known blind spots, and unresolved issues. Avoid unsupported labels such as clean, safe, or representative.
Limitations and risks
Document sampling bias, detector limitations, temporal limits, language/domain gaps, harmful content, privacy residuals, contamination risk, and inappropriate downstream uses.
Reproducibility
Provide immutable source, code, configuration, environment, and artifact identifiers sufficient for an authorised reviewer to reproduce the release.
Changes and withdrawal
Maintain an append-only version history with corrections, removals, licence changes, and downstream notification requirements.