Introduction to Transformer Models for NLP: Unit 3

Introduction to Transformer Models for NLP: Unit 3

本课程是 Introduction to Transformer Models for NLP 专项课程的一部分

位教师：Pearson

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1个模块

深入了解一个主题并学习基础知识。

中级等级

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5 小时完成

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1个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

5 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Understand and apply the T5 model’s end-to-end transformer architecture for advanced NLP tasks.
Fine-tune and evaluate transformer models for complex applications like abstractive summarization.
Leverage Vision Transformers and build custom image captioning systems by combining vision and language models.
Deploy, share, and operationalize transformer models using modern MLOps tools and cloud frameworks.

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作业

5 项作业

授课语言：英语（English）

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本课程是 Introduction to Transformer Models for NLP 专项课程专项课程的一部分

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该课程共有1个模块

This course covers transformer models and their applications in natural language processing and computer vision. Topics include the T5 model, fine-tuning for tasks such as abstractive summarization, and the Vision Transformer. Students will learn to build an image captioning system by combining vision and language models. The course also provides practical instruction on deploying models, including MLOps practices, sharing models on HuggingFace, and cloud deployment with FastAPI. By the end of the course, students will have the knowledge and skills to implement, fine-tune, and deploy transformer models for various real-world tasks.

This module explores advanced transformer models and their applications across natural language processing and computer vision. Learners will examine the T5 model’s end-to-end architecture and cross-attention mechanism, apply and fine-tune T5 for complex NLP tasks, and discover how vision transformers extend these techniques to image processing and image captioning. The module concludes with practical strategies for deploying and sharing transformer models using MLOps principles, HuggingFace, and FastAPI, equipping students with both theoretical understanding and hands-on skills for state-of-the-art model development and deployment.