🤖 Large Language Models (LLMs)

Name: 🤖 Large Language Models (LLMs)
Author: RahulSaini02

@RahulSaini02

🤖 Large Language Models (LLMs) について

This repo is dedicated to learning and working with large language models (LLMs), prompt engineering, and modern GenAI tools such as LangChain, RAG, and vector databases.

#mcp #transformers #transfer-learning #prompt-engineering #llms #langchain #mcp-server

基本情報

カテゴリ

メモリとナレッジ

トランスポート

stdio

公開者

RahulSaini02

設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is 🤖 Large Language Models (LLMs)?

This repository is a learning resource dedicated to large language models, prompt engineering, and modern generative AI tools such as LangChain, RAG, and vector databases.

How to use 🤖 Large Language Models (LLMs)?

Browse the folder structure to access learning materials on transformer architecture, prompt engineering strategies, and LangChain/RAG pipelines. No installation or configuration steps are described.

Key features of 🤖 Large Language Models (LLMs)?

Transformer architecture, pretraining vs finetuning, and Hugging Face models
Prompting strategies, few-shot prompting, and instruction tuning
LangChain pipelines, RAG systems, memory, tools, and vector databases

Use cases of 🤖 Large Language Models (LLMs)?

Learning the fundamentals of transformer models and fine-tuning
Mastering prompt engineering techniques for various tasks
Building retrieval-augmented generation (RAG) systems with Lang

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