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As language models become increasingly common, it becomes crucial to employ a broad set of strategies and tools in order to fully unlock their potential. Foremost among these strategies is prompt engineering, which involves the careful selection and arrangement of words within a prompt or query in order to guide the model towards producing theContinue reading "The LLM Triad: Tune, Prompt, Reward"
Applied Sciences March-1 2024 - Browse Articles
Gradient Flow
Understanding RLHF for LLMs
Introduction to LLM Model Fine Tuning
Understanding RLHF for LLMs
Finetuning an LLM: RLHF and alternatives (Part II)
A Comprehensive Guide to fine-tuning LLMs using RLHF (Part-1)
Some Core Principles of Large Language Model (LLM) Tuning, by Subrata Goswami
vocab.txt · imjliao/llm-embedder at main
NeurIPS 2022
Paper page - Directly Fine-Tuning Diffusion Models on Differentiable Rewards
Maximizing the Potential of Large Language Models - Gradient Flow