GhassenChawati1

Extensions:
• Dash to Dock
• Desktop Cube
• Compiz Windows Effect
• Compiz Alike Magic Lamp Effect
• Blur My Shell
Apps:

Extension Manager

karpathy

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

tianchaijz

## ifconfig

The ifconfig command is used to configure a network interface.

For a breakdown of the following ouput see: http://www.aboutlinux.info/2006/11/ifconfig-dissected-and-demystified.html

If you don't want to configure a network interface then running the command without any arguments will display existing network interfaces.

eth0      Link encap:Ethernet  HWaddr 0A:05:1E:A5:6F:FF  

Ev-ZHelak

Documentation courses ->

Простая структура класса

Пример:

tsl0922

# vim style tmux config

# use C-a, since it's on the home row and easier to hit than C-b
set-option -g prefix C-a
unbind-key C-a
bind-key C-a send-prefix
set -g base-index 1

# Easy config reload
bind-key R source-file ~/.tmux.conf \; display-message "tmux.conf reloaded."

k16shikano

name	japanese-tech-writing
description	日本語の技術文書・書籍原稿の文章規範。整形（一文一行、引用ブロック、脚注、コラム記法）、段落と論証の構成（パラグラフライティング）、論証の厳密さ（ツッコミどころの除去）、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。

日本語技術文書の文章規範

日本語で技術的な原稿（書籍の章、記事、解説文）を書く・推敲するときは、以下の規範に従う。

整形

marcusjhq2097u0

GameVision Assistant Pro

Practice with context. Review every decision.

An independent Windows training and replay-analysis assistant for Counter-Strike 2 and other FPS practice workflows.

DocShotgun

Performant local mixture-of-experts CPU inference with GPU acceleration in llama.cpp

Introduction

So you want to try one of those fancy huge mixture-of-experts (MoE) models locally? Well, whether you've got a gaming PC or a large multi-GPU workstation, we've got you covered. As long as you've downloaded enough RAM beforehand.

Anatomy of a MoE Model

MoE models are described in terms of their total parameters and active parameters - i.e. DeepSeek V3 671B A37B has 671B total parameters, but we are using only 37B parameters at a time during each forward pass through the model.