Slides

The following tutorials are mainly based on material provided by Hugging Face

Take a look at the slides tutorial to learn how to use all slide options.

You have several options to start code development:

  1. Colab: Click on one of the links “💻 Jupyter Notebook” to start a Colab session.

  2. Local: Click on one of the links “💻 Jupyter Notebook” below, go to the Colab menu and choose “File” > “Download” > “Download .ipynb”

  3. Cloud Codespace: Work in a fully configured dev environment in the cloud with a GitHub Codespace VS Code Browser environment.

  4. Local VS Code with Codespace: Use GitHub Codespaces in your local Visual Studio Code environment.

1 Hugging Face Hub

In this tutorial, you’ll get to know the Hugging Face Hub:

  • Explore the over models shared in the Hub.
  • Learn efficient ways to find the right model and datasets for your own task
  • Learn how to contribute and work collaboratively in your ML workflows

2 Build and Host Machine Learning Demos

In this tutorial, you’ll learn how to build and host Machine Learning Demos with Gradio ⚡ & Hugging Face:

  • Explore ML demos created by the community.
  • Build a quick demo for your machine learning model in Python using the gradio library
  • Host the demos for free with Hugging Face Spaces
  • How to add your demo to our Hugging Face org for your class

Optional resources:

3 Getting Started with Transformers

Learn how to use transformers in Hugging Face:

  • Transformer neural networks can be used to tackle a wide range of tasks in natural language processing and beyond.
  • Transfer learning allows one to adapt Transformers to specific tasks.
  • The pipeline() function from the transformers library can be used to run inference with models from the Hugging Face Hub.

Optional resources:

4 Sentiment Analysis

Learn how to perform sentiment analysis:

5 Summarization

Learn how to perform text summarization:

6 Question and Answering

Qestion answering tasks return an answer given a question:

7 Text generation

Text generation models:

8 Transformers intuition

Learn some basics about transformers models:

9 Diffusion models

Learn about the various use cases of diffusion models and how to use the diffusers library to use pre-trained state-of-the-art diffusion models:

Optional resources: