Natural Language Processing

This section documents text representation, sequence modeling, attention mechanisms, and Large Language Model (LLM) architectures.

Key Focus Areas

• Text Representations: Tokenization, Word2Vec, GloVe, subword embeddings.
• Sequence Modeling: Encoder-Decoder models, attention mechanisms, Transformer architecture.
• LLMs & Fine-Tuning: Prompt engineering, PEFT/LoRA, instruction tuning, and alignment techniques.

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Table of contents

• Overview of LLMs
• Building GPT from Scratch
• Diving Deep into LLMs