brauhaus

I maintain a Chrome extension that adds an AI support to any input field online.

One of my favorite reviews is a 2-star review asking for “local model support”.

My first reaction was: who installs a 100KB Chrome extension to talk to a 10GB model running locally?

But it did make me curious. Are people actually running Ollama or LM Studio as part of their daily workflow?

Imagine you have an open source project that got a major sponsor. What's the best way to fairly distribute this money among the team? Should it be based on contribution levels, time spent, or something else? What models have worked well for you?

Hey there!

As a backend dev who's been nosing around frontend land for my side projects, I'm curious to know how you approach your CSS

- Are paid templates your thing, or do you stick with the free stuff? - Bootstrap themes, or do you Tailwind it from scratch? - Do you reuse your styles or create a fresh one every time?

What works for you? What doesn't?

PS: Any must-have resources are also greatly appreciated! :)

I feel I'm ready to leave the Colab environment, and I wanted to start developing PyTorch projects on my local machine. The problem: I have a Windows machine with AMD Radeon GPU (cries in wsl)

What is the preferred way to get started? I've tried using WSL, ROCm, and PyTorch-DirectML, but I'm always running into problems when I run `to(device)`.

Context: my boss wants me to evaluate the skills and gaps of our dev team and suggest a "learning path" of _existing_ courses every new hire should take.

Our work is mostly with data and our new hires are usually DS fresh out of college. They know their stuff when it comes to using Python and Spark to create ML models, but they lack experience in how to work in teams. So I listed the following topics I find vital for them to learn.

- Git Branching Strategies - Clean Code - Design Patterns - Testing - MLflow - CI/CD - IDE configuration (linters, useful Text Editor add-ons) - Code documentation - Dealing with business requirements in code - Publishing packages at private repos - Code structure (cookiecutters, package managers) - Code smells - Antipatterns - How to code review effectively - Debugging

My challenge is that because the company subscribes to Coursera - and because they want the course to contain scored tests - they want me to select courses from there. I argued that it doesn't make sense to select university courses to fill a gap many universities don't cover (or didn't in my case). Plus their syllabuses are usually crap: how can I know, for instance, that when a course says it covers "OOP in Python", the Gang of Four design patterns will also be taught? Other than wasting hours going through courses by myself, that is.

So

What I needed here are suggestions of other resources I could try to lobby my superiors - from great Udemy courses or Youtube channels.