huggingface-paper-publisher

Name: huggingface-paper-publisher
Availability: InStock
Author: yanochka11

Publish and manage machine learning research papers on Hugging Face Hub repositories.

Updated May 5, 2026

Search Tags:#machine learning #citations #arxiv #huggingface #paper publishing #research articles

Ready to run

npx skills add https://github.com/yanochka11/harness_bro --skill huggingface-paper-publisher-yanochka11

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: huggingface-paper-publisher
Source: https://github.com/yanochka11/harness_bro/tree/main/.claude/skills/ported/huggingface-paper-publisher
Command: npx skills add https://github.com/yanochka11/harness_bro --skill huggingface-paper-publisher-yanochka11

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires huggingface_hub, pyyaml, requests, python-dotenv, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the complex workflow of publishing, linking, and managing AI research papers on the Hugging Face Hub, reducing manual metadata handling and repository updates.

Core Features & Use Cases

Paper Publishing Workflows: Index papers from arXiv, manage Hugging Face Paper Pages, and verify authorship claims.
Research Artifact Linking: Connect papers with Hugging Face models, datasets, and Spaces using proper metadata and citations.
Research Article Generation: Create structured markdown research articles with standard, modern, arXiv, and ML experiment report templates.
Use Case: A machine learning researcher can generate a publication-ready article, link an arXiv paper to a model repository, and create BibTeX citations from one workflow.

Quick Start

Use the huggingface-paper-publisher skill to create a modern research article template for my new machine learning paper and prepare it for Hugging Face publication.

Frequently Asked Questions about huggingface-paper-publisher

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

FAQPage Schema

How do I publish a machine learning research paper on the Hugging Face Hub?▼

Publishing a machine learning research paper on the Hugging Face Hub involves automating arXiv indexing, verifying authorship, and linking models or datasets. This skill streamlines that workflow by generating structured markdown articles and metadata for reproducible research publishing.

Can I generate BibTeX citations for my arXiv paper and Hugging Face models?▼

Yes, you can generate BibTeX citations for arXiv papers and Hugging Face models. The skill provides citation generation utilities that automatically connect your research artifacts using proper metadata to ensure accurate referencing.

What's the best way to link an arXiv paper to a Hugging Face model repository?▼

Linking an arXiv paper to a Hugging Face model repository requires applying proper metadata and citation tags. This skill automates research artifact linking, connecting your scientific articles directly with corresponding models and datasets on the Hub.

Do I need a Hugging Face API token to manage paper repositories and metadata?▼

Yes, Hugging Face API integration is required to manage paper repositories and handle metadata. You need to configure your environment with API credentials using python-dotenv to authenticate and automate article generation and publishing workflows.

What markdown templates are available for generating structured research articles?▼

Available markdown templates include standard, modern, arXiv, and ML experiment report formats. The skill creates structured research articles by applying these templates during the scientific article generation process for publication-ready outputs.

Why does my Hugging Face paper publishing workflow fail during authorship verification?▼

Hugging Face paper publishing workflows can fail during authorship verification if metadata is incomplete or API credentials are missing. The skill automates authorship claims by validating metadata handling, requiring valid Hugging Face API integration to succeed.