tuning – Andrew Fairless, Ph.D.

What I Read: Fine-tuning

By Andrew Fairless on December 11, 2024September 3, 2024

https://openpipe.ai/blog/fine-tuning-best-practices-series-introduction-and-chapter-1-training-data Fine-tuning Best Practices Series Introduction and Chapter 1: Training DataReid MayoAug 1, 2024 “We’ll explore how to choose the best data, common methods for collecting it, and common methodsContinue readingWhat I Read: Fine-tuning

What I Read: Evaluating LLM-Evaluators

By Andrew Fairless on December 3, 2024August 26, 2024

https://eugeneyan.com/writing/llm-evaluators Evaluating the Effectiveness of LLM-Evaluators (aka LLM-as-Judge)Eugene Yan “After reading this, you’ll gain an intuition on how to apply, evaluate, and operate LLM-evaluators. We’ll learn when to apply (i)Continue readingWhat I Read: Evaluating LLM-Evaluators

What I Read: LLM Pre-training Post-training

By Andrew Fairless on November 18, 2024August 26, 2024

https://magazine.sebastianraschka.com/p/new-llm-pre-training-and-post-training New LLM Pre-training and Post-training ParadigmsA Look at How Modern LLMs Are TrainedSebastian Raschka, PhDAug 17, 2024 “Initially, the LLM training process focused solely on pre-training, but it hasContinue readingWhat I Read: LLM Pre-training Post-training

What I Read: LLM evaluation

By Andrew Fairless on October 21, 2024July 22, 2024

https://hamel.dev/blog/posts/evals Your AI Product Needs EvalsHow to construct domain-specific LLM evaluation systems.Hamel HusainMarch 29, 2024 “…I’ve seen many successful and unsuccessful approaches to building LLM products. I’ve found that unsuccessfulContinue readingWhat I Read: LLM evaluation

What I Read: LLMs, Open Source

By Andrew Fairless on July 15, 2024May 6, 2024

https://www.aidancooper.co.uk/how-to-beat-proprietary-llms How to Beat Proprietary LLMs With Smaller Open Source ModelsAidan CooperApr 26, 2024 “…we explore the unique advantages of open source LLMs, and how you can leverage them toContinue readingWhat I Read: LLMs, Open Source

What I Read: Instruction Tuning

By Andrew Fairless on February 19, 2024December 19, 2023

https://gaotianyu.xyz/blog/2023/11/30/instruction-tuning/ Teach Llamas to Talk: Recent Progress in Instruction TuningTianyu Gao30 November 2023 “…open-ended instruction tuning… fine-tunes an LLM such that it can follow user instructions…. there have been numerousContinue readingWhat I Read: Instruction Tuning

What I Read: Enterprise AI, RAG + Fine Tuning

By Andrew Fairless on January 11, 2024November 20, 2023

https://www.montecarlodata.com/blog-the-moat-for-enterprise-ai-is-rag-fine-tuning/ The Moat for Enterprise AI is RAG + Fine Tuning – Here’s WhyLior GavishUpdated Nov 09 2023 “Data needs to be secure and private; LLM deployment needs to beContinue readingWhat I Read: Enterprise AI, RAG + Fine Tuning

What I Read: LLM Training, RLHF

By Andrew Fairless on October 30, 2023October 5, 2023

https://magazine.sebastianraschka.com/p/llm-training-rlhf-and-its-alternatives LLM Training: RLHF and Its AlternativesSebastian Raschka, PhDSep 10, 2023 “RLHF is an integral part of the modern LLM training pipeline due to its ability to incorporate human preferencesContinue readingWhat I Read: LLM Training, RLHF

What I Read: LLMs, single example

By Andrew Fairless on October 23, 2023September 9, 2023

https://www.fast.ai/posts/2023-09-04-learning-jumps/ Can LLMs learn from a single example?Jeremy Howard and Jonathan WhitakerSeptember 4, 2023 “We’ve noticed an unusual training pattern in fine-tuning LLMs. At first we thought it’s a bug,Continue readingWhat I Read: LLMs, single example

Tag: tuning