Hugging Face Inference API Overview

Get introduced to Hugging Face, transformers, and the Inference API.

Despite the groundbreaking performance of deep learning, there are a number of applied areas where many users either don’t have the background or don’t have time to code all the details. Hugging Face provides the perfect solution to this with their platform. Users can use a number of deep learning models without investing resources and time into learning all the underlying theories and complex details of the deep learning libraries.

Transformers

It's impossible to talk about Hugging Face (or any modern NLP model) without mentioning transformers. Transformers are the backbone of almost all of the Hugging Face modelsModels are programs trained on a dataset. They learn data patterns and make decisions for the unseen data.. Instead of classical recurrent neural networks (RNNs)-based models, they employ attention. In layman's terms, attention is a mechanism to give different weights to different parts of a sentence or a passage, and it provides excellent results.

Transformers' success in NLP made CV researchers curious and led to the creation of different models, such as vision transformers, which are used for CV tasks using Hugging Face.

Hugging Face Inference API

The Hugging Face Inference API provides NLP, CV, and audio processing models that can be conveniently accessed via a single API request. We can perform many complicated tasks by mitigating the technicalities of ML models. In this course, we’ll perform NLP and CV tasks by using the Hugging Face Inference API. The illustration below highlights the capabilities of this API:

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Hugging Face Inference API
Hugging Face Inference API