A comprehensive, interview-ready reference for SDE2 frontend system design interviews.
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| game:GetService("StarterGui"):SetCore("SendNotification", { | |
| Title = "Archived by toriko ;v"; | |
| Text = "All hail Toriko the certified ball sucker";}) | |
| Duration = 90; | |
| game:GetService("StarterGui"):SetCore("SendNotification", { |
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.
| cd\Program Files\Microsoft Office\Office16 | |
| cd\Program Files (x86)\Microsoft Office\Office16 | |
| cscript OSPP.VBS /sethst:kms.digiboy.ir | |
| cscript OSPP.VBS /actcscript OSPP.VBS /dstatus | |
| slmgr.vbs /ckms |
This script is designed to assist in identifying pull requests to HuggingFace repositories
that are sourced from the SFConvertbot user.
The SFConvertbot user is part of an automated tool used by HuggingFace to provide safetensor
versions of models. As published by HiddenLayer
this bot can be used by malicious actors to potentially insert malicious content into models.
This tool is a simple script to query all models released by a HuggingFace author, and checks all
