Does this skill require a Hugging Face token?

Yes, it uses the HF_TOKEN environment variable for authorized API calls to ensure higher rate limits and access to private or gated content.

What scripting languages are supported?

It prioritizes shell scripts for maximum shell-piping compatibility but can generate Python or TSX scripts for more complex logic.

Is it compatible with the new hf CLI?

Yes, it is designed to use the modern hf command line tool, which has replaced the deprecated huggingface_hub CLI.

How does it handle the large Hugging Face OpenAPI schema?

It uses targeted jq queries to extract specific endpoint information rather than attempting to process the entire multi-megabyte schema file at once.

Can it help find models associated with specific papers?

Yes, it includes specific patterns for searching the Hugging Face Hub by arXiv IDs and parsing relevant model card metadata.

Hugging Face Tool Builder

Name: Hugging Face Tool Builder
Author: lingxling

bylingxling

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Ciencia de Datos y ML

Builds reusable CLI scripts and shell-friendly utilities for interacting with the Hugging Face Hub API and ecosystem.

This skill empowers developers to automate complex Hugging Face Hub operations by generating composable, shell-friendly scripts and utilities. It facilitates seamless interaction with models, datasets, and spaces through direct API calls and the hf command-line tool, supporting advanced features like piping, NDJSON processing, and authenticated metadata extraction. By leveraging environment variables for security and jq for efficient data processing, it enables the creation of high-performance tools for managing machine learning assets at scale.

Características Principales

01Automated creation of CLI scripts for model and dataset management

02Efficient API exploration using jq to handle large OpenAPI schemas

03Standardized script generation with built-in help documentation

04Support for chaining and piping outputs for complex data pipelines

0539 GitHub stars

06Secure authentication handling using the HF_TOKEN environment variable

Casos de Uso

01Building search utilities to find models based on specific arXiv paper IDs

02Automating bulk metadata extraction from model cards into structured JSON

03Creating data enrichment pipelines that stream Hub metadata to external tools

Características Principales

01Automated creation of CLI scripts for model and dataset management

02Efficient API exploration using jq to handle large OpenAPI schemas

03Standardized script generation with built-in help documentation

04Support for chaining and piping outputs for complex data pipelines

0539 GitHub stars

06Secure authentication handling using the HF_TOKEN environment variable

Casos de Uso

01Building search utilities to find models based on specific arXiv paper IDs

02Automating bulk metadata extraction from model cards into structured JSON

03Creating data enrichment pipelines that stream Hub metadata to external tools