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Llm Wiki | Skills Pool

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Llm Wiki

Conceitos fundamentais de LLMs. Ativar quando discutir tokens, contexto, temperatura, RAG, agentes, escolha de modelo.

Andersonlimahw0 starsApr 14, 2026

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Categories: LLM & AI

Skill Content

LLM Wiki — Conceitos Essenciais

Baseado em: https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f Skills: https://skills.sh | https://www.aitmpl.com/skills

Tokens e Contexto

~4 chars/token em inglês, ~2-3 em português
Context window: limite total de tokens (entrada + saída)
Informação no meio do contexto pode ser esquecida ()

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Llm Wiki

npx skillvault add Andersonlimahw/andersonlimahw-ai-starter-kit-templates-gemini-skills-llm-wiki-skill-md

Download Skill Open repository

Author: Andersonlimahw
stars: 0
Updated: Apr 14, 2026
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On this page

01LLM Wiki — Conceitos Essenciais

lost in the middle

Temperatura

0: determinístico (código, dados) | 0.7+: criativo (texto)

Agentes

ReAct: Reason → Act → Observe (loop)
Subagents: especializados, chamados pelo orquestrador
Custo: proporcional a turnos × tokens

RAG vs Fine-tuning

RAG: contexto em runtime, bom para conhecimento mutável
Fine-tuning: estilo/formato, não para fatos novos

Modelos (Gemini)

Gemini 2.5 Pro: arquitetura, decisões críticas
Gemini 2.0 Flash: implementação, equilíbrio custo/qualidade
Gemini 2.0 Flash Lite: formatação, boilerplate

Referências

https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f
https://skills.sh | https://www.aitmpl.com/skills

02

Tokens e Contexto

05RAG vs Fine-tuning

06Modelos (Gemini)

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