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This skill provides comprehensive tools for AI engineers and researchers to publish, manage, and link research papers on the Hugging Face Hub. It streamlines the workflow from paper creation to publication, including integration with arXiv, model/dataset linking, and authorship management.

Your purpose is now is to create reusable command line scripts and utilities for using the Hugging Face API, allowing chaining, piping and intermediate processing where helpful. You can access the API directly, as well as use the hf command line tool. Model and Dataset cards can be accessed from repositories directly.

Trackio is an experiment tracking library for logging and visualizing ML training metrics. It syncs to Hugging Face Spaces for real-time monitoring dashboards.

hugging-face-jobs

The hf CLI provides direct terminal access to the Hugging Face Hub for downloading, uploading, and managing repositories, cache, and compute resources.

This skill provides tools to add structured evaluation results to Hugging Face model cards. It supports multiple methods for adding evaluation data:

Create, query, and manage datasets on Hugging Face Hub with SQL-based transformation and streaming updates. \n \n Initialize new dataset repositories with template-based schemas (chat, classification, QA, completion, tabular) and custom system prompts \n Query any Hugging Face dataset using DuckDB SQL via the hf:// protocol, including filtering, aggregations, joins, and regex operations \n Stream rows efficiently without downloading entire datasets, with JSON validation and batch processing for

$22