hugging-face-dataset-viewer – skill Dữ liệu & Khoa học cho agent AI
Hugging Face Dataset Viewer
Cài skill hugging-face-dataset-viewer bằng một lệnh
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Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/hugging-face-dataset-viewer-21c17.tgz | tar xz -C ~/.claude/skills
Gọi trong Claude Code: /hugging-face-dataset-viewer – rồi mô tả công việc bạn muốn làm.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/hugging-face-dataset-viewer-21c17.tgz | tar xz -C ~/.codex/skills
Gọi trong Codex: $hugging-face-dataset-viewer – rồi mô tả công việc bạn muốn làm.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/hugging-face-dataset-viewer-21c17.tgz | tar xz -C ~/.hermes/skills
Gọi trong Hermes Agent: /hugging-face-dataset-viewer – rồi mô tả công việc bạn muốn làm.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/hugging-face-dataset-viewer-21c17.tgz | tar xz -C ~/.deepcode/skills
Gọi trong DeepSeek: /hugging-face-dataset-viewer – rồi mô tả công việc bạn muốn làm.
Nội dung SKILL.md
Nội dung SKILL.md gốc bằng tiếng Anh.
Hugging Face Dataset Viewer
When to Use
Use this skill when you need 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.
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
Session traces can contain private prompts, files, secrets and third-party data. A Dataset Viewer request does not authorize uploading history. For an explicitly requested trace upload, select only named sessions, create a redacted export, verify permission/retention and the actual destination visibility, and keep raw originals private. An existing repo may remain public even when a create command includes --private/--exist-ok; inspect visibility before transmission.
hf repos create <namespace>/<repo> --type dataset --private --exist-ok
hf upload <namespace>/<repo> /absolute/reviewed-redacted-export codex/<selected-project> --type datasetLimitations
- Use this skill only when the task clearly matches its upstream product or API scope.
- Verify commands, API behavior, pricing, quotas, credentials, and deployment effects against current official documentation before making changes.
- Do not treat generated examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.
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