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Basics of Reinforcement Learning for LLMs
Understanding the problem formulation and basic algorithms for RL..
 • 
Cameron R. Wolfe, Ph.D.
2
RLAIF: Reinforcement Learning from AI Feedback
Making alignment via RLHF more scalable by automating human feedback...
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Cameron R. Wolfe, Ph.D.
Understanding and Using Supervised Fine-Tuning (SFT) for Language Models
Understanding how SFT works from the idea to a working implementation...
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Cameron R. Wolfe, Ph.D.
3
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Advanced Prompt Engineering
 • Cameron R. Wolfe, Ph.D.
6
Specialized LLMs: ChatGPT, LaMDA, Galactica, Codex, Sparrow, and More
 • Cameron R. Wolfe, Ph.D.
2
Language Models: GPT and GPT-2
 • Cameron R. Wolfe, Ph.D.
Practical Prompt Engineering
 • Cameron R. Wolfe, Ph.D.
5
Graph-Based Prompting and Reasoning with Language Models
 • Cameron R. Wolfe, Ph.D.
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Language Model Training and Inference: From Concept to Code
Learning and implementing next token prediction with a casual language model...
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Cameron R. Wolfe, Ph.D.
Graph-Based Prompting and Reasoning with Language Models
Understanding graph of thoughts prompting and several variants...
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Cameron R. Wolfe, Ph.D.
Tree of Thoughts Prompting
Solving multi-step problems with LLMs via deliberate planning and exploration...
 • 
Cameron R. Wolfe, Ph.D.
LLaMA-2 from the Ground Up
Everything you need to know about the best open-source LLM on the market...
 • 
Cameron R. Wolfe, Ph.D.
2
The History of Open-Source LLMs: Imitation and Alignment (Part Three)
Open-source LLMs need alignment to become truly remarkable...
 • 
Cameron R. Wolfe, Ph.D.
2
The History of Open-Source LLMs: Better Base Models (Part Two)
How LLaMA, MPT, Falcon, and LLaMA-2 put open-source LLMs on the map...
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Cameron R. Wolfe, Ph.D.
3
The History of Open-Source LLMs: Early Days (Part One)
Understanding GPT-Neo, GPT-J, GLM, OPT, BLOOM, and more...
 • 
Cameron R. Wolfe, Ph.D.
3
Deep (Learning) Focus
Deep (Learning) Focus
I contextualize and explain important topics in AI research.
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