huggingface-datasets

by huggingface

Install this Skill

curl -fsSL -o huggingface-datasets.zip https://skill.seembox.com/api/v1/skills/huggingface-datasets/download && unzip huggingface-datasets.zip

Download huggingface-datasets.zip

SKILL.md About

---
name: huggingface-datasets
description: 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.
---

# 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-ok
hf upload <namespace>/<repo> ~/.codex/sessions codex/<project-or-cwd> --type dataset
```