Agent skill

huggingface-datasets

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.

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Install this agent skill to your Project

npx add-skill https://github.com/huggingface/skills/tree/main/skills/huggingface-datasets

SKILL.md

Hugging Face Dataset Viewer

Use this skill to execute read-only Dataset Viewer API calls for dataset exploration and extraction.

Core workflow

  1. Optionally validate dataset availability with /is-valid.
  2. Resolve config + split with /splits.
  3. Preview with /first-rows.
  4. Paginate content with /rows using offset and length (max 100).
  5. Use /search for text matching and /filter for row predicates.
  6. Retrieve parquet links via /parquet and totals/metadata via /size and /statistics.

Defaults

  • Base URL: https://datasets-server.huggingface.co
  • Default API method: GET
  • Query params should be URL-encoded.
  • offset is 0-based.
  • length max is usually 100 for 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:

bash
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:

  • /search matches string columns (full-text style behavior is internal to the API).
  • /filter requires predicate syntax in where and optional sort in orderby.
  • Keep filtering and searches read-only and side-effect free.

Querying Datasets

Use npx parquetlens with Hub parquet alias paths for SQL querying.

Parquet alias shape:

text
hf://datasets/<namespace>/<repo>@~parquet/<config>/<split>/<shard>.parquet

Derive <config>, <split>, and <shard> from Dataset Viewer /parquet:

bash
curl -s "https://datasets-server.huggingface.co/parquet?dataset=cfahlgren1/hub-stats" \
  | jq -r '.parquet_files[] | "hf://datasets/\(.dataset)@~parquet/\(.config)/\(.split)/\(.filename)"'

Run SQL query:

bash
npx -y -p parquetlens -p @parquetlens/sql parquetlens \
  "hf://datasets/<namespace>/<repo>@~parquet/<config>/<split>/<shard>.parquet" \
  --sql "SELECT * FROM data LIMIT 20"

SQL export

  • CSV: --sql "COPY (SELECT * FROM data LIMIT 1000) TO 'export.csv' (FORMAT CSV, HEADER, DELIMITER ',')"
  • JSON: --sql "COPY (SELECT * FROM data LIMIT 1000) TO 'export.json' (FORMAT JSON)"
  • Parquet: --sql "COPY (SELECT * FROM data LIMIT 1000) TO 'export.parquet' (FORMAT PARQUET)"

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:
bash
curl -s "https://datasets-server.huggingface.co/parquet?dataset=<namespace>/<repo>"

Low dependency CLI flow (npx @huggingface/hub / hfjs):

  • Set auth token:
bash
export HF_TOKEN=<your_hf_token>
  • Upload parquet folder to a dataset repo (auto-creates repo if missing):
bash
npx -y @huggingface/hub upload datasets/<namespace>/<repo> ./local/parquet-folder data
  • Upload as private repo on creation:
bash
npx -y @huggingface/hub upload datasets/<namespace>/<repo> ./local/parquet-folder data --private

After upload, call /parquet to discover <config>/<split>/<shard> values for querying with @~parquet.

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