Welcome to the Hugging Face Documentation section! Here, you will find comprehensive resources to help you get started with Hugging Face and its models.
Quick Start
If you are new to Hugging Face, here's a quick guide to get you started:
- Install the Hugging Face Python package:
pip install transformers - Load a pre-trained model:
from transformers import AutoModel - Use the model for inference:
model = AutoModel.from_pretrained("bert-base-uncased")
For more detailed instructions, check out the Installation Guide.
Models Overview
Hugging Face offers a wide range of pre-trained models for various natural language processing tasks. Here are some popular models:
- BERT: A general-purpose pre-trained language representation model.
- GPT-3: A powerful language model capable of generating human-like text.
- T5: A transformer-based model for text-to-text tasks.
For a complete list of models, visit the Models Hub.
API Reference
Hugging Face provides an API for easy integration of models into your applications. Here's a brief overview of the API:
- Model Loading: Load a model from the Hub using
AutoModel.from_pretrained(). - Inference: Use the model for inference with
model.generate().
For more information on the API, see the API Documentation.
Learn More
For further reading, you can explore the following resources: