The visualization of two approaches to fine-tune LLMs based on
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A High-level Overview of Large Language Models - Borealis AI
Carl YANG, University of Illinois, Urbana-Champaign, IL, UIUC, Department of Computer Science
目前有哪些方式训练一个领域的大语言模型？ Beyond One-Model-Fits-All A Survey of Domain Specialization LLM - 知乎
Improving any OpenAI Language Model by Systematically Improving
Carl YANG, University of Illinois, Urbana-Champaign, IL, UIUC, Department of Computer Science
Chen LING, Doctor of Philosophy, Emory University, GA, EU, Department of Mathematics and Computer Science
Tanmoy CHOWDHURY, PhD Student, Master of Science, George Mason University, VA, GMU, Department of Information Sciences and Technology
The History of Open-Source LLMs: Imitation and Alignment (Part Three)
Finetuning Falcon LLMs More Efficiently With LoRA and Adapters
Fine-Tuning LLMs: In-Depth Analysis with LLAMA-2
Carl YANG, University of Illinois, Urbana-Champaign, IL, UIUC, Department of Computer Science
The LLM Triad: Tune, Prompt, Reward - Gradient Flow
21 Ways to Fine Tune Your Contact Centre
Fine-Tuning Large Language Models for Decision Support: A Comprehensive Guide, by Anthony Alcaraz
How to Fine-tune Llama 2 with LoRA for Question Answering: A Guide for Practitioners
