Huggingface Datasets

作者 huggingfaceabc20ae526d8无许可证11K 个星标收录于 2026年10月8日更新于 2026年10月8日仓库今天更新

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.

仅含说明Data & Analytics
AI 生成的概览

指导使用 Hugging Face Dataset Viewer API 进行只读的数据集浏览、搜索、筛选与行数据获取。

功能
该技能记录了 Hugging Face Dataset Viewer API 的工作流程,涵盖验证数据集、列出子集与拆分、预览首行、分页获取行、文本搜索、按条件筛选,以及获取 parquet 链接、大小总计和列统计等接口。它还说明了创建和上传数据集的方式,包括 parquet 上传和智能体会话轨迹,并指出用于继续获取部分结果的分页字段。其产出是 API 请求及获取到的数据集元数据或行数据,而非本地文件。
适用场景
当你需要通过 Dataset Viewer API 查看或提取 Hugging Face 数据集时使用,例如解析 config 与 split、分页读取行数据,或执行文本搜索与筛选。它也适用于将 parquet 文件或智能体轨迹上传到数据集仓库的场景。
运行要求
需要访问 Hugging Face Dataset Viewer API 和 Hub 的网络连接。受限或私有数据集需要 HF_TOKEN 持有者凭证。上传流程使用 Hub 网页界面或 npx @huggingface/hub,轨迹流程使用 hf CLI。该技能不包含脚本,仅为说明文档。

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.

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:
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.

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.

bash
hf repos create <namespace>/<repo> --type dataset --private --exist-okhf upload <namespace>/<repo> ~/.codex/sessions codex/<project-or-cwd> --type dataset

来源与署名

来源:huggingface/skills位于skills/huggingface-datasets提交abc20ae

许可证: 无许可证

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