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carpelbr4323

様々なローカルLLM(Qwen、Gemma)を活用する方法を学習し、LLMシステムの性能を効率的に評価(Evaluation)し改善する様々な技法を見ていきます。

aischool

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ローカルLLM（Local LLM）活用ガイド Part 1 - small LLM（sLLM）の活用 & LLMの性能評価（Evaluation）および改善

실습 중심

ai in practice

AI 활용법

에이전트

Learn how to utilize various local LLMs (Qwen, Gemma) and explore different techniques to efficiently evaluate and improve the performance of LLM systems.

AISchool

입문

초급

중급이상

대규모 언어 모델

랭체인

LangChain

AI 에이전트

AI Agent

랭그래프

LangGraph

Local LLM Utilization Guide Part 1 - Using small LLM(sLLM) & Evaluating and Improving LLM Performance

Lecture 1 - Overview of Open Source Local LLM & small LLM(sLLM)

Lecture 2 - LLM Model Performance Evaluation Overview

Setting up the practice environment

Task 1 - Comparing the translation performance of local LLM models

Task 2 - Comparing the MRC QA performance of local LLM models

Task 3 - Building a RAG (Retrieval-Augmented Generation) System with Local LLM Models

Task 4 - Evaluating the Web Search Tool Usage Capabilities of Local LLM Models

Task 5 - Building an AI Agent by Integrating a Local LLM Model with LangGraph

Task 6 - Comparing the Moderation Performance of Local LLM Models

Task 7 - Comparing the Mathematical Reasoning Performance of Local LLM Models

Task 8 - Comparing the Text-to-SQL Performance of Local LLM Models