hugging-face-dataset-creator

Create and manage Hugging Face dataset repositories with validated JSONL training examples.

2|Updated May 20, 2026
One-click install
npx skills add https://github.com/Dianshu-Liao/SkilLGuard --skill hugging-face-dataset-creator-dianshu-liao
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: hugging-face-dataset-creator
Source: https://github.com/Dianshu-Liao/SkilLGuard/tree/main/data/skills/hf_dataset_creator
Command: npx skills add https://github.com/Dianshu-Liao/SkilLGuard --skill hugging-face-dataset-creator-dianshu-liao

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires huggingface_hub, and includes scripts (resource) components.

What problem does it solve?

This Skill removes the friction of creating and maintaining Hugging Face dataset repositories by providing a repeatable workflow for repository setup, configuration, and incremental row uploads with template-based validation.

Core Features & Use Cases

  • Dataset lifecycle management: initialize dataset repos, write configuration (including system prompts), and stream updates by uploading JSONL row chunks.
  • Template-driven dataset formats: generate validated training data structures for chat/conversational, classification, QA, completion, tabular data, and fully custom schemas.
  • Quality safeguards: validate JSON rows against template schemas and provide clear error handling for malformed JSON, missing fields, and upload issues.

Quick Start

Use the hugging-face-dataset-creator skill to initialize a private dataset repo and add a small validated batch of rows using the chat template.

Frequently Asked Questions about hugging-face-dataset-creator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create and stream JSONL training examples to a Hugging Face dataset repository?

To create and stream JSONL training examples to a Hugging Face dataset repository, you can use a CLI script that initializes the repo, writes system configuration, and streams validated row chunks using HF_TOKEN authentication.

What dataset formats are supported when generating validated training data for Hugging Face?

Supported dataset formats include chat/conversational, classification, QA, completion, tabular data, and fully custom schemas, all validated against template schema rules before uploading to Hugging Face.

Do I need an HF_TOKEN to automate dataset uploads and repository management on Hugging Face?

Yes, you need an HF_TOKEN to authenticate Hugging Face Hub API operations for initializing dataset repositories, writing configurations, and streaming JSONL row chunks.

How does template validation handle malformed JSON or missing fields during dataset curation?

Template validation checks JSON rows against defined validation_schema rules and provides clear error handling for malformed JSON, missing fields, and upload issues during dataset curation.

Can I use custom schemas and local templates for Hugging Face dataset creation?

Yes, you can generate custom schema-based datasets using local templates and example sets, allowing flexible dataset creation beyond standard conversational or classification formats.