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Rachasumanth
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model-publisher

Package trained AI models and publish them to Hugging Face Hub.

Updated Feb 17, 2026
Search Tags:#mlops#gguf#safetensors#hugging face#model card#model publishing
One-click install
npx skills add https://github.com/Rachasumanth/text2llm001 --skill model-publisher
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: model-publisher
Source: https://github.com/Rachasumanth/text2llm001/tree/main/workspace/skills/model-publisher
Command: npx skills add https://github.com/Rachasumanth/text2llm001 --skill model-publisher

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of packaging trained AI models, generating essential documentation like model cards, and publishing them to platforms like Hugging Face Hub, simplifying model distribution and collaboration.

Core Features & Use Cases

  • Checkpoint Packaging: Converts training checkpoints to SafeTensors, ensuring integrity and compatibility.
  • Model Card Generation: Automatically creates comprehensive README.md files detailing model usage, architecture, training data, and limitations.
  • Hugging Face Hub Publishing: Manages repository creation, artifact uploads, and versioned updates using huggingface-cli.
  • Optional GGUF Export: Generates quantized GGUF variants for efficient local inference.
  • Use Case: A machine learning engineer has just finished training a new natural language processing model and needs to share it with their team. They use this Skill to package the model, generate a detailed model card, and publish it to a private Hugging Face repository.

Quick Start

Use the model-publisher skill to package and publish the latest trained model to Hugging Face Hub.

Frequently Asked Questions about model-publisher

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

FAQPage Schema
How do I package and publish a trained model to Hugging Face Hub?▼

To package and publish a trained model to Hugging Face Hub, you can automate checkpoint conversion to SafeTensors, auto-generate model cards, and use Hugging Face CLI integration for release management and repository uploads.

What is the best way to generate a model card for AI models?▼

Generating a model card for AI models is automated by creating comprehensive README files detailing model usage, architecture, training data, and limitations, which simplifies model documentation and distribution.

Can I convert training checkpoints to SafeTensors before publishing?▼

Yes, you can convert training checkpoints to SafeTensors during the packaging phase to ensure artifact integrity and compatibility before uploading the model to the Hugging Face Hub repository.

Does Hugging Face publishing support GGUF export for local inference?▼

Hugging Face publishing supports optional GGUF export, allowing you to generate quantized GGUF variants from your trained model for efficient local inference and distribution.

Do I need a Hugging Face token to automate model publishing?▼

Yes, you need a Hugging Face token to automate model publishing, as the process validates your Hugging Face token and verifies repository access permissions before initiating the upload.

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