Skip to content

Instantly share code, notes, and snippets.

View zerothabhishek's full-sized avatar

Abhishek Yadav zerothabhishek

View GitHub Profile
@Rich-Harris
Rich-Harris / what-is-svelte.md
Last active June 11, 2026 19:55
The truth about Svelte

I've been deceiving you all. I had you believe that Svelte was a UI framework — unlike React and Vue etc, because it shifts work out of the client and into the compiler, but a framework nonetheless.

But that's not exactly accurate. In my defense, I didn't realise it myself until very recently. But with Svelte 3 around the corner, it's time to come clean about what Svelte really is.

Svelte is a language.

Specifically, Svelte is an attempt to answer a question that many people have asked, and a few have answered: what would it look like if we had a language for describing reactive user interfaces?

A few projects that have answered this question:

@onlurking
onlurking / programming-as-theory-building.md
Last active July 27, 2026 00:58
Programming as Theory Building - Peter Naur

Programming as Theory Building

Peter Naur

Peter Naur's classic 1985 essay "Programming as Theory Building" argues that a program is not its source code. A program is a shared mental construct (he uses the word theory) that lives in the minds of the people who work on it. If you lose the people, you lose the program. The code is merely a written representation of the program, and it's lossy, so you can't reconstruct

@noseratio
noseratio / async-generator.js
Last active March 28, 2021 22:09
Async generators and "for await" in JavaScript
// by @noseratio
// https://twitter.com/noseratio/status/1297517388552757249?s=20
// gist: https://gist.github.com/noseratio/721fea7443b74a929ea93c8f6a18cec4/edit
// RunKit: https://runkit.com/noseratio/async-generators-and-for-await-in-javascript
async function delay(ms) {
await new Promise(r => setTimeout(r, ms));
return ms;
}
@shawwn
shawwn / llama_sizes.txt
Created March 5, 2023 18:07
The size of each file distributed with LLaMA, for reference. See https://github.com/shawwn/llama-dl
./tokenizer_checklist.chk 50
./tokenizer.model 499723
./7B/checklist.chk 100
./7B/consolidated.00.pth 13476939516
./7B/params.json 101
./13B/checklist.chk 154
./13B/consolidated.00.pth 13016334699
./13B/consolidated.01.pth 13016334699
./13B/params.json 101
./30B/checklist.chk 262
@rohitg00
rohitg00 / llm-wiki.md
Last active August 2, 2026 03:59 — forked from karpathy/llm-wiki.md
LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory

LLM Wiki v2

A pattern for building personal knowledge bases using LLMs. Extended with lessons from building agentmemory 20K+ Stars ⭐️, a persistent memory engine for AI coding agents.

This builds on Andrej Karpathy's original LLM Wiki idea file. Everything in the original still applies. This document adds what we learned running the pattern in production: what breaks at scale, what's missing, and what separates a wiki that stays useful from one that rots.

What the original gets right

The core insight is correct: stop re-deriving, start compiling. RAG retrieves and forgets. A wiki accumulates and compounds. The three-layer architecture (raw sources, wiki, schema) works. The operations (ingest, query, lint) cover the basics. If you haven't read the original, start there.