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
- Install Hugging Face
- Use pre-trained models
- Fine-tune a model
- 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.