AI Text Summarization with Hugging Face

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Janani Ravi

2:05:41

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01 - Introduction

01 - AI Text Summarization with Hugging Face.mp4

06:02

02 - 1. Understanding Extractive Text Summarization

01 - Prerequisites.mp4

01:06

02 - Extractive text summarization.mp4

02:34

03 - Intermediate representations for extractive summarization.mp4

07:04

04 - Evaluation metrics for summaries.mp4

02:57

03 - 2. Performing Extractive Text Summarization Using Hugging Face

01 - Exploring Hugging Face.mp4

04:45

02 - Signing up for Hugging Face.mp4

00:59

03 - The sumy library for extractive summarization.mp4

03:36

04 - Extractive text summarization on Hugging Face.mp4

05:32

04 - 3. Understanding Abstractive Text Summarization

01 - Abstractive text summarization.mp4

02:32

02 - Abstractive summarization using the Hosted Inference API on Hugging Face.mp4

05:39

05 - 4. Understanding Transformers

01 - Sequence-to-sequence models.mp4

04:13

02 - Attention in sequence-to-sequence models.mp4

02:59

03 - A brief introduction to Transformers.mp4

03:55

04 - Transformers in Hugging Face.mp4

05:24

06 - 5. Performing Summarization Using a Hugging Face Pipeline

01 - Using Colab to work with Hugging Face Transformers.mp4

03:07

02 - Loading the CNN Daily Mail dataset.mp4

06:05

03 - Cleaning text data.mp4

02:10

04 - Generating summaries with Hugging Face Transformers.mp4

05:27

05 - Evaluating summaries using ROUGE scores.mp4

03:49

06 - Summarizing text and computing aggregate ROUGE scores.mp4

04:09

07 - 6. Fine-Tuning a Transformer Model for Summarization

01 - Understanding tokenizers.mp4

03:01

02 - Fine-tuning the T5 small model.mp4

07:10

03 - Pushing the model to the Hugging Face Hub.mp4

02:48

04 - Summarizing text using the fine-tuned model.mp4

06:46

08 - 7. Exploring Different Hugging Face Transformers for Summarization

01 - Accessing the BBC dataset on Google Drive.mp4

03:34

02 - Instantiating and cleaning the BBC News summaries dataset.mp4

03:48

03 - Generating summaries using Pegasus.mp4

04:55

04 - Generating multiple summaries and computing aggregate ROUGE scores.mp4

02:49

05 - Generating summaries using BART.mp4

03:19

06 - Computing ROUGE metrics for a set of summaries.mp4

02:09

09 - Conclusion

01 - Summary and next steps.mp4

01:18

Description

The Hugging Face AI community aspires to advance and democratize artificial intelligence through open source and open science. In this course, Janani Ravi guides you through using this powerful AI tool to summarize text. Learn how extractive text summarization works, as well as its intermediate representations. Explore evaluation metrics, and find out how to navigate and access information on the Hugging Face platform. Go over logging into Hugging Face, using the sumy library for extractive summarization, and using abstractive text summarization with the Hosted Inference API. Learn about sequence-to-sequence models, transformers, and how to use them in Hugging Face. Plus, dive into using a Hugging Face pipeline to perform actual summarization, fine-tuning a transformer model, and exploring several Hugging Face transformers.

This course was created by Janani Ravi. We are pleased to host this training in our library.

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Artificial Intelligence

Janani Ravi

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