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AI lessons (37/37)

AI — Hugging Face

What is Hugging Face?

Platform for sharing and using ML models.

Install

pip install transformers datasets

Use Pre-trained Model

from transformers import pipeline

# Sentiment analysis
classifier = pipeline("sentiment-analysis")
result = classifier("I love this!")

# Text generation
generator = pipeline("text-generation", model="gpt2")
text = generator("Once upon a time")

Fine-tuning

from transformers import AutoModelForSequenceClassification, Trainer

model = AutoModelForSequenceClassification.from_pretrained("bert-base")
trainer = Trainer(model=model, train_dataset=dataset)
trainer.train()

Datasets

from datasets import load_dataset

dataset = load_dataset("imdb")

Mini Practice

  1. Install Hugging Face
  2. Use pre-trained models
  3. Fine-tune a model
  4. Explore datasets

Up Next

Continue with Model Training — training models.

Related Topics

Frequently Asked Questions about Hugging Face

What is Hugging Face in AI?

Hugging Face is a fundamental concept in AI. This lesson explains it step by step with clear examples, making it easy for beginners to understand.

How do I learn Hugging Face?

Start by reading the explanation above, then try the code examples. Practice by modifying the examples and experimenting with different values. Hands-on practice is the best way to learn Hugging Face.

Why is Hugging Face important in AI?

Hugging Face is essential for AI development. Understanding this concept will help you write better code and solve real-world problems more effectively.