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I'm gonna use this article to explain to my peers about LLM quantization!

They are different quantization types, you can read more here https://huggingface.co/docs/hub/gguf#quantization-types

you just answered your own question, "AI hobbyists who has 4090 at home". And they are pretty much targeted user of Unsloth since the start.


Actually the opposite haha- more than 50% of our audience comes from large organizations eg Meta, NASA, the UN, Walmart, Spotify, AWS, Google, and the list goes on!


I've tried both. Each has pros and cons. Two things I don't like about superpowers is it writes all the codes into the implementation plan, at the plan step, then the subagents basically just rewrite these codes back to the files. And I have to ask Claude to create a progress.md file to track the progress if I want to work in multiple sessions. GSD pretty much solved these problems for me, but the down side of GSD is it takes too many turns to get something done.


There is a fork that uses Claude Code-native features and tracks progress and task dependencies natively: https://github.com/pcvelz/superpowers


If you use it I'm curious if you find it limited at all from lagging behind superpowers? For instance I opened up one skill at random and they haven't yet pulled in the latest commit from last week.

I doubt any hot off the press features are *that* important, but am curious if the customizations of the fork are a net positive considering this.


Bangle is a good one https://banglejs.com/ Quite fun to work with. I got one from a conference, and my kid has been enjoying it a lot.


Wonder if you could get Clojure (through the SCI) running on it.

How is the general watch API? The development experience?

is there some community or list of exciting projects made for it? for inspiration :)


When your watch supports the most common computer language on Earth, it is hard to go wrong with it. 4 week standby is pretty good too.


Bangle doesn't have standalone wifi...


exactly what i think when reading the top of the article, maybe the author turned off vebose mode


The verbose mode is, well, verbose. They removed, without any need, info and hid it in a wall of text.


Joke about train line aside, I think Railway fits right in the spot that Heroku left.

They have a nice UI, support deploy any kind of backend-involved apps as long as it can be built into a docker container. While many PaaS out there seems to prioritize frontend only apps.

And they have a free plan, so people can just quickly deploy some POC before decide if it's good to move on.

Anyone know if there is any other PaaS that come with a low cost starter plan like this (a side from paying for a VPS)?


Been building an open source version of railway at https://canine.sh. Offers all the same features without the potential of a vendor lock-in / price gouging.


The docs seem to be non existent. Is the canine yaml documented?

You want docs like this:

https://coolify.io/docs/applications/ci-cd/github/setup-app

https://coolify.io/docs/applications/build-packs/dockerfile

https://coolify.io/docs/applications/build-packs/overview

Plenty of screenshots and exact step by step instructions. Throwing an "example git repo" with no documentation won't get you any users.

Put your shoes into that of a Heroku/Vercel user. DevOps is usually Somebody Else's Problem. They are not going to spend hours debugging kubernetes so if you want to sell them a PaaS built on Kubernetes, it has to be fool proof. Coolify is an excellent example, the underlying engineering is average at best (from a pure engineering point of view it's a very heavy app that suffers from frequent memory leaks, they have a new v5 rewrite but it's been stuck for 2 years) but the UI/UX has been polished very well.


Yeah working through documentation still. The goal isn’t so much to replace coolify. Mostly born out of my last start up that ran a $20M business, 15 engineers, with about 300-1000qps at peak, with fairly complex query patterns.

I think the single VPS model is just too hard to get working right at that scale.

I think north flank / enterprise applications, would be a better comparison of what canine is trying to do, rather than coolify / indie hackers. The goal is not take away kubernetes, but to simplify it massively for 90% of use cases but still give full k8s api for any more advanced features


> Computing is getting cheaper

Heh.

Looks like a great product, although maybe mention some honest reasons to not use it, instead of the passive-aggressive marketing ones.


Render.com has a similar value proposition. I’ve used them and am pretty happy. Railway seems to have more bundled observability built in, that i’d like in render.


Yes, have you seen miget.com by any chance? You can start with the free tier, and can have a backend with a database for free (256Mi plan). If you need more, just upgrade. They redefined cloud billing. Worth checking.


VPS + Dokploy gives you just as much functionality with an additional performance boost. Hostinger has great prices and a one-click setup. Good for dozens of small projects.


+1 for dokploy, it's very flexible and allows me to setup my sites how I need. Especially as it concerns to the way I setup a static landing page, then /app goes to the react app. And /auth goes to a separate auth service, etc.


I use https://github.com/coollabsio/coolify on a VPS for this.


Context: This is Railway the PaaS company, not your daily commute vehicle (which is good in general, still bad for many users, like me).


A global train outage would be quite a spectacle, is that even possible?


Yeah, i probs should have made that clear


> Due to a miscommunication with the factory, the injection pins were moved inside the heatsink fins, causing the cylindrical extrusions below.

What happened after this? the factory have to replace the casting mold at their own expense or you have to pay for it?


We had to remake half the mold, and I split it 50/50 with the factory.


I was hoping for the /v1/messages endpoint to use with Claude Code without any extra proxies :(


This is a breeze to do with llama.cpp, which has had Anthropic responses API support for over a month now.

On your inference machine:

  you@yourbox:~/Downloads/llama.cpp/bin$ ./llama-server -m <path/to/your/model.gguf> --alias <your-alias> --jinja --ctx-size 32768 --host 0.0.0.0 --port 8080 -fa on
Obviously, feel free to change your port, context size, flash attention, other params, etc.

Then, on the system you're running Claude Code on:

  export ANTHROPIC_BASE_URL=http://<ip-of-your-inference-system>:<port>
  export ANTHROPIC_AUTH_TOKEN="whatever"
  export CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1
  claude --model <your-alias> [optionally: --system "your system prompt here"]
Note that the auth token can be whatever value you want, but it does need to be set, otherwise a fresh CC install will still prompt you to login / auth with Anthropic or Vertex/Azure/whatever.


yup, I've been using llama.cpp for that on my PC, but on my Mac I found some cases where MLX models work best. haven't tried MLX with llama.cpp, so not sure how that will work out (or if it's even supported yet).


Well, to whoever downvoted my comment: It's supported now!!!! https://lmstudio.ai/blog/claudecode


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