huggingface-datasets
Skill547 starsChanged 3 months agoMITView on GitHub
Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.
We split this skill into the rules it gives an agent
10 rules. 4 are common, 0 are distinctive, and 6 are very specific to this project.
4
Common
Most of the 9 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
6
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 9
Use this skill to execute read-only Dataset Viewer API calls for dataset exploration and extraction.
- Very specific: line 17
Use /search for text matching and /filter for row predicates.
- Very specific: line 23
Default API method: GET
- Very specific: line 49
When pagination is partial, use response fields such as num_rows_total, num_rows_per_page, and partial to drive continuation logic.
- Common: line 55
Keep filtering and searches read-only and side-effect free.
- Common: line 61
Use one of these flows depending on dependency constraints.
- Very specific: line 65
Create dataset repo in browser: https://huggingface.co/new-dataset
- Common: line 67
Verify shards appear in Dataset Viewer:
- Very specific: line 93
After upload, call /parquet to discover <config>/<split>/<shard> values for querying with @~parquet.
- Very specific: line 103
Default to private dataset repos because traces can contain prompts, file paths, tool outputs, secrets, or PII.
“Common” is measured: kept by at least 6 in 10 of the 9 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Hugging Face Dataset Viewer
Use this skill to execute read-only Dataset Viewer API calls for dataset exploration and extraction.
Core workflow
- Optionally validate dataset availability with
/is-valid. - Resolve
config+splitwith/splits. - Preview with
/first-rows. - Paginate content with
/rowsusingoffsetandlength(max 100). - Use
/searchfor text matching and/filterfor row predicates. - Retrieve parquet links via
/parquetand totals/metadata via/sizeand/statistics.
Defaults
- Base URL:
https://datasets-server.huggingface.co - Default API method:
GET - Query params should be URL-encoded.
offsetis 0-based.lengthmax is usually100for row-like endpoints.- Gated/private datasets require
Authorization: Bearer <HF_TOKEN>.
Dataset Viewer
Validate dataset:/is-valid?dataset=<namespace/repo>List subsets and splits:/splits?dataset=<namespace/repo>Preview first rows:/first-rows?dataset=<namespace/repo>&config=<config>&split=<split>Paginate rows:/rows?dataset=<namespace/repo>&config=<config>&split=<split>&offset=<int>&length=<int>Search text:/search?dataset=<namespace/repo>&config=<config>&split=<split>&query=<text>&offset=<int>&length=<int>Filter with predicates:/filter?dataset=<namespace/repo>&config=<config>&split=<split>&where=<predicate>&orderby=<sort>&offset=<int>&length=<int>List parquet shards:/parquet?dataset=<namespace/repo>Get size totals:/size?dataset=<namespace/repo>Get column statistics:/statistics?dataset=<namespace/repo>&config=<config>&split=<split>Get Croissant metadata (if available):/croissant?dataset=<namespace/repo>
Pagination pattern:
curl "https://datasets-server.huggingface.co/rows?dataset=stanfordnlp/imdb&config=plain_text&split=train&offset=0&length=100"
curl "https://datasets-server.huggingface.co/rows?dataset=stanfordnlp/imdb&config=plain_text&split=train&offset=100&length=100"When pagination is partial, use response fields such as num_rows_total, num_rows_per_page, and partial to drive continuation logic.
Search/filter notes:
/searchmatches string columns (full-text style behavior is internal to the API)./filterrequires predicate syntax inwhereand optional sort inorderby.- Keep filtering and searches read-only and side-effect free.
For CLI-based parquet URL discovery or SQL, use the hf-cli skill with hf datasets parquet and hf datasets sql.
Creating and Uploading Datasets
Use one of these flows depending on dependency constraints.
Zero local dependencies (Hub UI):
- Create dataset repo in browser:
https://huggingface.co/new-dataset - Upload parquet files in the repo "Files and versions" page.
- Verify shards appear in Dataset Viewer:
curl -s "https://datasets-server.huggingface.co/parquet?dataset=<namespace>/<repo>"Low dependency CLI flow (npx @huggingface/hub / hfjs):
- Set auth token:
export HF_TOKEN=<your_hf_token>- Upload parquet folder to a dataset repo (auto-creates repo if missing):
npx -y @huggingface/hub upload datasets/<namespace>/<repo> ./local/parquet-folder data- Upload as private repo on creation:
npx -y @huggingface/hub upload datasets/<namespace>/<repo> ./local/parquet-folder data --privateAfter upload, call /parquet to discover <config>/<split>/<shard> values for querying with @~parquet.
Agent Traces
The Hub supports raw agent session traces from Claude Code, Codex, and Pi Agent. Upload them to Hugging Face Datasets as original JSONL files and the Hub can auto-detect the trace format, tag the dataset as Traces, and enable the trace viewer for browsing sessions, turns, tool calls, and model responses. Common local session directories:
- Claude Code:
~/.claude/projects - Codex:
~/.codex/sessions - Pi:
~/.pi/agent/sessions
Default to private dataset repos because traces can contain prompts, file paths, tool outputs, secrets, or PII. Preserve the raw .jsonl files and nest them by project/cwd instead of uploading every session at the dataset root.
hf repos create <namespace>/<repo> --type dataset --private --exist-ok
hf upload <namespace>/<repo> ~/.codex/sessions codex/<project-or-cwd> --type datasetOther versions9 projects use a version of this.
Word for word · 0
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Edited · 8
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Wrote their own version · 1
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How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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