Hugging Face Overview
Understand the Hugging Face ecosystem and its core components like Transformers, pretrained models, and pipelines. Learn how these tools simplify applying advanced NLP and computer vision models. This lesson covers the evolution of transformers, the role of pretrained models, and how pipelines enable efficient AI workflows with minimal coding.
We'll cover the following...
Hugging Face is far more than a single library; it represents a comprehensive ecosystem designed to make modern machine learning accessible, practical, and collaborative.
At its core, Hugging Face provides tools and libraries that span natural language processing, computer vision, audio, and multimodal AI, allowing developers, researchers, and hobbyists to experiment, fine-tune, and deploy models without needing to master every underlying algorithm from scratch.
The ecosystem consists of several key components that work together seamlessly.
The Transformers library provides pre-trained models, ranging from classical NLP models like BERT and RoBERTa to modern large language models (LLMs) like Llama and Falcon.
The Datasets library simplifies access to curated datasets and provides tools for preparing data efficiently for training or inference. ...