I often keep trying to implement architectures, and papers from first principles or ‘from-scratch’ as it’s more commonly known today. Instead of creating multiple ’nn_test’ colab notebooks, I decided to begin adding them to a repo, not just to have them on my git, but also as a quick refresher I can keep looking back to. A screen grab of my self-masked attention implementation ...
Ferret is a python cli-tool that lets you ‘ferret through’ project repositories, analyze their directory structure and get AI based explanations on them. Features List files and folders as a tree Explain the directory structure using an LLM (OpenAI API) (Gemini/Claude/HF coming soon) Generate module import dependency graph as a Mermaid chart To view the code and docs, check my git: https://github.com/abishekpadaki/ferret
(last updated: 11th Aug 2025) There are a ton of benchmarks already present for reasoning llms, but I have a very simple one (just a single prompt for now) that I use, every time a new reasoning model is released. It’s a logical pattern discovering question based on Pokemon and various generations’ starters. The prompt goes as follows: This is a puzzle for you to solve the missing Pokemon based on a pattern. Figure out the pattern in the examples I provide by thinking carefully and hard. Here are the examples to begin with: ...