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Large Language Models
·
Module 4
Foundational Transformer Architectures
1
The Original Transformer Architecture
Describe the original encoder-decoder Transformer architecture from 'Attention Is All You Need'.
2
Self-Attention vs. Cross-Attention in Encoder-Decoder Models
Distinguish between self-attention and cross-attention, and identify where each is used in an encoder-decoder model.
3
Decoder-Only Transformers for Generation
Describe the decoder-only architecture (e.g., GPT series) and its suitability for generative tasks.
4
Encoder-Only Models: BERT and Understanding-Based Tasks
Describe the encoder-only architecture (e.g., BERT) and its suitability for understanding-based tasks.
5
Comparing Transformer Architectures: Training and Applications
Compare encoder-only, decoder-only, and encoder-decoder architectures in terms of their training objectives and typical applications.
Previous module
Building the Transformer Block
Next module
Language Modeling and Training Objectives