Learn Hugging Face by Building a Custom AI Model
6h 32m 55s
English
Paid
Course description
Explore the Hugging Face ecosystem from scratch, including Transformers, Datasets, Hub/Spaces, and much more, by creating and configuring your own AI model for text classification. In this course, you will learn how to deploy your model for real-world use!
Watch Online
0:00
/ #1: Introduction (Hugging Face Ecosystem and Text Classification)
All Course Lessons (39)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 1 | Introduction (Hugging Face Ecosystem and Text Classification) Demo | 06:53 | |
| 2 | More Text Classification Examples | 04:41 | |
| 3 | What We're Going To Build! | 07:22 | |
| 4 | Getting Setup: Adding Hugging Face Tokens to Google Colab | 05:53 | |
| 5 | Getting Setup: Importing Necessary Libraries to Google Colab | 09:36 | |
| 6 | Downloading a Text Classification Dataset from Hugging Face Datasets | 16:01 | |
| 7 | Preparing Text Data for Use with a Model - Part 1: Turning Our Labels into Numbers | 12:49 | |
| 8 | Preparing Text Data for Use with a Model - Part 2: Creating Train and Test Sets | 06:19 | |
| 9 | Preparing Text Data for Use with a Model - Part 3: Getting a Tokenizer | 12:54 | |
| 10 | Preparing Text Data for Use with a Model - Part 4: Exploring Our Tokenizer | 10:27 | |
| 11 | Preparing Text Data for Use with a Model - Part 5: Creating a Function to Tokenize Our Data | 17:58 | |
| 12 | Setting Up an Evaluation Metric (to measure how well our model performs) | 08:54 | |
| 13 | Introduction to Transfer Learning (a powerful technique to get good results quickly) | 07:11 | |
| 14 | Model Training - Part 1: Setting Up a Pretrained Model from the Hugging Face Hub | 12:20 | |
| 15 | Model Training - Part 2: Counting the Parameters in Our Model | 12:27 | |
| 16 | Model Training - Part 3: Creating a Folder to Save Our Model | 03:54 | |
| 17 | Model Training - Part 4: Setting Up Our Training Arguments with TrainingArguments | 15:00 | |
| 18 | Model Training - Part 5: Setting Up an Instance of Trainer with Hugging Face Transformers | 05:06 | |
| 19 | Model Training - Part 6: Training Our Model and Fixing Errors Along the Way | 13:35 | |
| 20 | Model Training - Part 7: Inspecting Our Models Loss Curves | 14:40 | |
| 21 | Model Training - Part 8: Uploading Our Model to the Hugging Face Hub | 08:02 | |
| 22 | Making Predictions on the Test Data with Our Trained Model | 05:59 | |
| 23 | Turning Our Predictions into Prediction Probabilities with PyTorch | 12:49 | |
| 24 | Sorting Our Model's Predictions by Their Probability | 05:11 | |
| 25 | Performing Inference - Part 1: Discussing Our Options | 09:41 | |
| 26 | Performing Inference - Part 2: Using a Transformers Pipeline (one sample at a time) | 10:02 | |
| 27 | Performing Inference - Part 3: Using a Transformers Pipeline on Multiple Samples at a Time (Batching) | 06:39 | |
| 28 | Performing Inference - Part 4: Running Speed Tests to Compare One at a Time vs. Batched Predictions | 10:34 | |
| 29 | Performing Inference - Part 5: Performing Inference with PyTorch | 12:07 | |
| 30 | OPTIONAL - Putting It All Together: from Data Loading, to Model Training, to making Predictions on Custom Data | 34:29 | |
| 31 | Turning Our Model into a Demo - Part 1: Gradio Overview | 03:48 | |
| 32 | Turning Our Model into a Demo - Part 2: Building a Function to Map Inputs to Outputs | 07:08 | |
| 33 | Turning Our Model into a Demo - Part 3: Getting Our Gradio Demo Running Locally | 06:47 | |
| 34 | Making Our Demo Publicly Accessible - Part 1: Introduction to Hugging Face Spaces and Creating a Demos Directory | 08:02 | |
| 35 | Making Our Demo Publicly Accessible - Part 2: Creating an App File | 12:15 | |
| 36 | Making Our Demo Publicly Accessible - Part 3: Creating a README File | 07:08 | |
| 37 | Making Our Demo Publicly Accessible - Part 4: Making a Requirements File | 03:34 | |
| 38 | Making Our Demo Publicly Accessible - Part 5: Uploading Our Demo to Hugging Face Spaces and Making it Publicly Available | 18:44 | |
| 39 | Summary Exercises and Extensions | 05:56 |
Unlock unlimited learning
Get instant access to all 38 lessons in this course, plus thousands of other premium courses. One subscription, unlimited knowledge.
Learn more about subscriptionComments
0 commentsWant to join the conversation?
Sign in to commentSimilar courses
Parsing Algorithms
Sources: udemy, Dmitry Soshnikov
Parsing or syntactic analysis is one of the first stages in designing and implementing a compiler. A well-designed syntax of your programming language is a big
4 hours 27 minutes 33 seconds
Break Into Tech And Become A Software Engineer
Sources: Brian Jenney
Career change and transition into the tech industry is a challenging task, but it is quite achievable with the right approach. In this course, you will learn...
1 hour 49 minutes 25 seconds
Software Engineering Beginner Fundamentals
Sources: Caleb Curry
Why is it important to start with the basics? A successful software engineer must possess a wide range of knowledge and skills. However, to avoid getting...
14 hours 43 minutes 9 seconds
Programming: Beyond the Basics
Sources: Oz Nova (csprimer.com)
There are countless ways to write any program. This course is designed so that you have all the tools necessary for fully expressing your ideas through...
11 hours 14 minutes 57 seconds
Smart Interface Design Patterns
Sources: Vitaly Friedman, smashingmagazine.com
Master essential design patterns for modern interfaces. Learn best practices through examples and live projects to tackle real-life challenges effectively.
13 hours 18 minutes 5 seconds