hugging-face-dataset-viewer

source	https://github.com/huggingface/skills/tree/main/skills/huggingface-datasets
name	hugging-face-dataset-viewer
description	Query Hugging Face datasets through the Dataset Viewer API for splits, rows, search, filters, and parquet links.
risk	unknown

Hugging Face Dataset Viewer

When to Use

Use this skill when you need read-only exploration of a Hugging Face dataset through the Dataset Viewer API.

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:

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:

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

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

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:

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:

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 --private

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

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for enprojectnment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.