Hugging Face has revolutionized AI and NLP by providing pre-trained models, datasets, and tools that simplify deep learning workflows. One of its most powerful capabilities is the ability to fine-tune pre-trained models for custom tasks.

This guide covers everything you need to know about Hugging Face and fine-tuning a model, including:

1. What is Hugging Face?
2. Why Fine-Tune a Model?
3. Understanding the Hugging Face Model Hub
4. Step-by-Step Guide to Fine-Tuning a Hugging Face Model
   • Text Classification
   • Named Entity Recognition (NER)
   • Question Answering
5. Optimizing Fine-Tuned Models
6. Deploying Fine-Tuned Models
7. Best Practices and Use Cases

1. What is Hugging Face?

Overview

Hugging Face provides a large collection of pre-trained models for NLP, computer vision, and speech tasks through its 🤗 Transformers library.

Hugging Face Ecosystem

• Transformers – Library for pre-trained models
• Datasets – Collection of datasets for ML training
• Model Hub – 100,000+ AI models
• Spaces – Deploy models with Gradio or Streamlit

2. Why Fine-Tune a Hugging Face Model?