AI Text Summarization with Hugging Face

Introduction

• AI Text Summarization with Hugging Face

1. Understanding Extractive Text Summarization

• Prerequisites
• Extractive text summarization
• Intermediate representations for extractive summarization
• Evaluation metrics for summaries

2. Performing Extractive Text Summarization Using Hugging Face

• Exploring Hugging Face
• Signing up for Hugging Face
• The sumy library for extractive summarization
• Extractive text summarization on Hugging Face

3. Understanding Abstractive Text Summarization

• Abstractive text summarization
• Abstractive summarization using the Hosted Inference API on Hugging Face

4. Understanding Transformers

• Sequence-to-sequence models
• Attention in sequence-to-sequence models
• A brief introduction to Transformers
• Transformers in Hugging Face

5. Performing Summarization Using a Hugging Face Pipeline

• Using Colab to work with Hugging Face Transformers
• Loading the CNN Daily Mail dataset
• Cleaning text data
• Generating summaries with Hugging Face Transformers
• Evaluating summaries using ROUGE scores
• Summarizing text and computing aggregate ROUGE scores

6. Fine-Tuning a Transformer Model for Summarization

• Understanding tokenizers
• Fine-tuning the T5 small model
• Pushing the model to the Hugging Face Hub
• Summarizing text using the fine-tuned model

7. Exploring Different Hugging Face Transformers for Summarization

• Accessing the BBC dataset on Google Drive
• Instantiating and cleaning the BBC News summaries dataset
• Generating summaries using Pegasus
• Generating multiple summaries and computing aggregate ROUGE scores
• Generating summaries using BART
• Computing ROUGE metrics for a set of summaries

Conclusion

• Summary and next steps