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Understanding Fine-Tuning of Large Language Models: A Comprehensive Overview
Tech (전영훈) YoungHoon Tech (전영훈) YoungHoon

Understanding Fine-Tuning of Large Language Models: A Comprehensive Overview

Fine-tuning Large Language Models (LLMs) is crucial for customizing AI to meet specific business needs. This blog delves into the two primary types of fine-tuning: instruction tuning, which enhances a model's ability to follow complex commands, and alignment tuning, which ensures outputs align with human values. By understanding these processes, businesses can effectively leverage AI for customer support, content creation, and more.

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Tech (전영훈) YoungHoon Tech (전영훈) YoungHoon

SAAS - Solving Ability Amplification Strategy for Enhanced Mathematical Reasoning in Large Language Models

Introducing "SAAS: Solving Ability Amplification Strategy for Enhanced Mathematical Reasoning in Large Language Models," a groundbreaking research paper by Upstage AI, Mathpresso Inc., and KT Corp. This novel approach leverages sequential learning, combining Chain-of-Thought (CoT) and Program-of-Thought (PoT) methodologies to significantly boost the mathematical reasoning and problem-solving skills of Large Language Models (LLMs). Our findings show that SAAS achieves state-of-the-art performance on benchmarks like GSM8K and MATH, outperforming larger models and setting new standards in AI-driven mathematical reasoning. Discover how SAAS can elevate your LLM’s capabilities.

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