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1
Intro
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Overview
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Key Points
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Pretraining
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Multitask model
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Setting up data
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Format data to input text
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Preparing the dataset
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T5 module
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Optimizer
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Test Case
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Python Trainer
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Sample Answers
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Key Results
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Time and Space
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Output vs Output
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Question Answering
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Question
Description:
Explore an in-depth introduction to T5 for sentiment span extraction in this hour-long talk by Lorenzo Ampil. Gain insights into the text-to-text approach of T5, its potential impact on NLP in industry, and its application in sentiment analysis of tweets. Learn about the model's architecture, pretraining process, and multitask capabilities. Follow along as Ampil demonstrates data preparation, setting up the T5 module, optimization techniques, and practical implementation using Python. Discover key results, compare outputs, and engage in a question-answering session to deepen your understanding of this cutting-edge NLP technology.

Introduction to T5 for Sentiment Span Extraction

Abhishek Thakur
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