Build Your First Hugging Face Mini-App
Explore building simple Hugging Face mini-apps that apply pretrained models for tasks such as text classification and image recognition. Learn how to implement pipelines, handle inputs and outputs, and customize models to create interactive applications that demonstrate end-to-end machine learning workflows.
Now that you understand Hugging Face pipelines, it’s time to put theory into practice. In this lesson, you’ll build a simple, interactive mini-app that uses a Hugging Face pipeline to process text or images. This hands-on experience will solidify your understanding of pipelines, model selection, and inference.
Why build a mini-app?
Many developers and data scientists understand models but struggle to deploy them in real-world scenarios. Mini-apps help bridge that gap:
Demonstrate end-to-end usage of models.
Provide interactive feedback for experimentation.
Teach you how to handle inputs, outputs, and parameters in a live setting.
Fun fact: Even the simplest Hugging Face app can give you the power of GPT, BERT, or ViT in just a few lines of code!
Step 1: Choose your task
Before writing code, decide what your mini-app will do, choosing from common options which include: