Search⌘ K
Home
Courses
Build AI Applications with LangChainGo

Hugging Face

Explore Hugging Face's platform to access pretrained transformer models and its Hosted Inference API. Learn to integrate Hugging Face APIs in Go for tasks like question answering and sentence similarity with step-by-step code examples and explanations.

We'll cover the following...

Introduction to Hugging Face

Hugging Face is a platform and community for machine learning focused on open-source tools and resources for building applications with transformers.

  • Pretrained transformers: Access a vast library of pretrained transformer models for various tasks, from natural language processing and computer vision to audio processing. Save time and resources by fine-tuning these models instead of training them from scratch.

  • Open-source collaboration: All models and tools on Hugging Face are open-source, allowing developers to inspect, modify, and share their creations. This fosters collaboration and innovation within the AI community.

  • Transformers library: The transformers library provides a unified API for accessing and fine-tuning models across different frameworks like PyTorch and TensorFlow. This simplifies development and makes working with transformers more efficient.

  • Curated datasets: Find high-quality text and image datasets for AI model training. Additionally, prebuilt tokenizers for various languages and tasks facilitate data preprocessing.

Hugging Face offers a couple of options for deploying and hosting models:

  1. Inference Endpoints: A production-grade solution to deploy models on dedicated infrastructure managed by Hugging Face.

  2. Hosted Inference API: This is a cost-effective serverless offering for accessing models deployed to a serverless shared infrastructure. We will ...