Do I need a Hugging Face token to use this skill?

While many public models are accessible without one, you will need a token to access gated models or private repositories. You can set this via the HUGGINGFACE_TOKEN environment variable.

Does this skill support computer vision and audio tasks?

Yes, it includes specific installation patterns and guidance for using libraries like timm, Pillow, librosa, and soundfile for non-text tasks.

What is the fastest way to get started with inference?

The Pipeline API is the recommended quick-start method, allowing you to run tasks like text generation or classification with just a few lines of code.

Can I fine-tune models directly using this skill?

Absolutely. The skill provides detailed patterns for using the Trainer API, including configuration for training arguments and dataset handling.

Hugging Face Transformers

Name: Hugging Face Transformers
Author: Weiwei-Mao

byWeiwei-Mao

Data Science & ML

Simplifies working with pre-trained transformer models for NLP, computer vision, and audio tasks within Claude Code.

About

The Transformers skill integrates the power of the Hugging Face ecosystem into Claude Code, providing standardized patterns for loading, fine-tuning, and deploying state-of-the-art AI models. It streamlines complex workflows—from simple inference using high-level pipelines to advanced model training with the Trainer API—across text, image, and audio domains. This skill is essential for developers and researchers looking to implement sophisticated AI capabilities like text generation, sentiment analysis, and object detection with production-grade best practices.

Key Features

Full support for fine-tuning pre-trained models on custom datasets
Advanced text generation control with custom decoding strategies
High-level Pipeline API for rapid inference across dozens of tasks
0 GitHub stars
Multimodal capabilities covering computer vision, audio, and NLP
Standardized model and tokenizer management with Hugging Face Hub integration

Use Cases

Implementing automated image tagging and object detection workflows
Building custom conversational AI or text summarization tools
Fine-tuning classification models on proprietary domain-specific data

About

Key Features

Full support for fine-tuning pre-trained models on custom datasets
Advanced text generation control with custom decoding strategies
High-level Pipeline API for rapid inference across dozens of tasks
0 GitHub stars
Multimodal capabilities covering computer vision, audio, and NLP
Standardized model and tokenizer management with Hugging Face Hub integration

Use Cases

Implementing automated image tagging and object detection workflows
Building custom conversational AI or text summarization tools
Fine-tuning classification models on proprietary domain-specific data