Sentencepiece Tokenizer With Offsets for T5, ALBERT, XLM-RoBERTa and Many More
Offered By: Abhishek Thakur via YouTube
Course Description
Overview
Learn how to implement Google's Sentencepiece tokenizer with offsets for question-answering systems in this 25-minute video tutorial. Discover techniques for using this tokenizer with ALBERT and other transformer-based models, while modifying data processing functions from previous lessons. Explore encoding, offsets, and class format data as you follow along with practical code examples. Access the complete implementation on Kaggle and build upon your knowledge from related tutorials on transformer models and question-answering systems.
Syllabus
Introduction
First Guest
The Problem
Encoding
Offsets
Class
Format Data
Outro
Taught by
Abhishek Thakur
Related Courses
Sentiment Analysis with Deep Learning using BERTCoursera Project Network via Coursera Natural Language Processing with Attention Models
DeepLearning.AI via Coursera Fine Tune BERT for Text Classification with TensorFlow
Coursera Project Network via Coursera Deploy a BERT question answering bot on Django
Coursera Project Network via Coursera Generating discrete sequences: language and music
Ural Federal University via edX