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Bringing Transformers to Life: Training & Inference

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Overview

You'll combine all Transformer components into a complete model, prepare synthetic datasets, implement autoregressive training with teacher forcing, and explore different decoding strategies for sequence generation.

Syllabus

  • Unit 1: Assembling the Transformer Model
    • Building Your First Transformer Model
    • Implementing Attention Boundaries
    • Your Transformer Comes Alive
  • Unit 2: Data Preparation and Tokenization
    • Building Your First Vocabulary System
    • Building Your Translation Dataset
    • Building Your Translation Dataset
    • Dynamic Padding for Sequence Batches
    • Building Your Complete Data Pipeline
  • Unit 3: Transformer Training Essentials
    • Building Your First Training Foundation
    • Building Smart Training Schedules
    • Building the Training Engine
    • Complete Your Training Script
  • Unit 4: Transformer Sequence Generation
    • Creating Your First Text Generator
    • Perfect Timing for Text Generation
    • Implementing Core Beam Search Logic
    • Exploring Beam Search Tradeoffs

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