selinux, zstd, flatpak, thinkfan, thinkpad t430, thinkpad t480, tailscale, vscode, nix, rpm-fusion, disable network connectivity check, battery charge threshold, gnome, nautilus, ptyxis-terminal, boxes, celluloid, declarative system changes
Discover gists
使用JAV金鸡儿奖官网附带的工具JAV SQL 查询器,可查询各种类别的JavDB TOP250影片:
及分年数据(存在部分重复影片,原始数据的问题):
| Cheef's Grand APDU List Smartcard Selected Information APDU list | |
| Reference: http://web.archive.org/web/20090630004017/http://cheef.ru/docs/HowTo/APDU.info | |
| #------------+------------------------+------------------------+----------------------+--------------------------------+ | |
| |ClaIns P1 P2|Lc Send Data |Le Recv Data | Specification | Description | | |
| +------------+------------------------+------------------------+----------------------+--------------------------------+ | |
| | 04 | ISO 7816-9 6.3 | DEACTIVATE FILE | | |
| | A0 04 00 00 00 | 3GPP TS 11.11 | INVALIDATE | | |
| | A0 04 00 00 00 | SAGEM SCT U34 6.15 | INVALIDATE | | |
| +------------+------------------------+------------------------+----------------------+--------------------------------+ |
A hands-on one semester course where students build their own compiler from scratch, starting from elementwise programs and ending with training SOTA LLMs on GPUs. This course aggressively builds on the previous week, and is an exercise in slop management. If you let any slop in early, it will compound and you will not finish the class.
Course description: This course covers the design and implementation of a modern machine learning compiler, and examines the interaction between IR design, hardware capabilities, and the structure of machine learning programs. Topics covered include term rewriting, code generation, movement operators, kernel fusion, memory hierarchies, GPU architecture, automatic differentiation, and flash attention. It is a project course, providing experience with performance-oriented programming, managing a codebase that grows all semester, and working in 1 or 2 person teams, culminating in a compiler capable of training modern LLMs.
Prerequisites: This c
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.
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.
لقد ضبطت المشكلة تماماً يا عرّاب من واقع سجل الأخطاء في الطرفية (Terminal Report).الخطأ RuntimeError: no running event loop يحدث بسبب معايير بايثون الحديثة (إصدار Python 3.14 الظاهر في السجل لديك)، حيث يرفض محرك الـ websockets الاستدعاء دون وجود حلقة أحداث مفعّلة ونشطة مسبقاً داخل نفس الـ Thread.بالإضافة إلى ذلك، لاحظت من السجل وجود مجلد جديد تعمل عليه الآن باسم Youtube_SPK كمسار جذر للمشروع.إليك شفرة الخادم النظيفة والمحدثة بالكامل المتوافقة 100% مع بايثون 3.14 ومجلدك الجديد لتشغيل المحرك بضغطة واحدة:🚀 كود المحرك السيادي المطور لبايثون 3.14 (stargate_launcher_v5.py)pythonimport os import sys import subprocess import time import json import asyncio from flask import Flask, request, jsonify, send_file from flask_cors import CORS from threading import Thread import websockets
| # 取得したドメインのDNS設定を完了しておく(TTL : 1800) | |
| # Ubuntu 22.04 はインストールしておく | |
| # 必要なものを root でインストールとリポジトリ追加 | |
| sudo apt install nginx-full gnupg2 openjdk-11-jdk curl apt-transport-https | |
| sudo apt-add-repository universe | |
| sudo apt update | |
| # ホスト名の設定 | |
| sudo hostnamectl set-hostname meet.example.com |
