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afshinea/stanford-cme-295-transformers-large-language-models

stanford-cme-295-transformers-large-language-models

VIP cheatsheet for Stanford's CME 295 Transformers and Large Language Models

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Mar 23, 2025

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README Summary

This repository contains a VIP (Very Important Points) cheatsheet for Stanford's CME 295 course on Transformers and Large Language Models. It serves as a comprehensive reference guide covering key concepts, architectures, and techniques related to transformer models and LLMs. The cheatsheet is designed to help students quickly review and understand the most important material from the course.

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Transformer ArchitectureLarge Language Model TheoryDeep Learning FundamentalsNatural Language ProcessingAttention MechanismsNeural Network Architecture Design

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Large Language Models Transformer Models Foundation Models

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Transformer Architecture Large Language Model Theory Deep Learning Fundamentals Natural Language Processing Attention Mechanisms Neural Network Architecture Design

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Academic Study Guide Course Reference Material Transformer Concepts Review LLM Theory Learning

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Updated 8 months ago

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Project created: Mar 23, 2025
Forked: Nov 16, 2025
Your last push: 8 months ago
Upstream last push: 8 months ago
Tracked since: Jul 27, 2025

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