projectmoon

Rclone can do file mounts as well as sync.

I feel like this article is exactly the type of thing it’s criticizing.

The problem is that while LLMs can translate, it’s still machine translation and isn’t always accurate. It’s also not going to just be for that. It’ll be applying “AI” to everything that looks like it might vaguely fit, and it’ll stifle productivity.

1 scenario tested is better than 0 tested.

This guy would fit in well at my previous job where the founder discouraged writing unit tests because “there are too many scenarios to test.”

Like, wtf…

It’s enough to run quantized versions of the distilled r1 model based on Qwen and Llama 3. Don’t know how fast it’ll run though.

For stuff like that, it’s best to have an auto formatter like checkstyle or something.

Had a team lead that kept requesting nitpicky changes, going in a FULL CIRCLE about what we should change or not, to the point that changes would take weeks to get merged. Then he had the gall to say that changes were taking too long to be merged and that we couldn’t just leave code lying around in PRs.

Jesus fucking Christ.

There’s a reason that team imploded…

They can build a keyboard into it, sure. It’s just UI elements and a bunch of buttons. Won’t be a good keyboard, but it can be done.

LLMs are statistical word association machines. Or tokens more accurately. So if you tell it to not make mistakes, it’ll likely weight the output towards having validation, checks, etc. It might still produce silly output saying no mistakes were made despite having bugs or logic errors. But LLMs are just a tool! So use them for what they’re good at and can actually do, not what they themselves claim they can do lol.

OpenWebUI connected tabbyUI’s OpenAI endpoint. I will try reducing temperature and seeing if that makes it more accurate.

Context was set to anywhere between 8k and 16k. It was responding in English properly, and then about halfway to 3/4s of the way through a response, it would start outputting tokens in either a foreign language (Russian/Chinese in the case of Qwen 2.5) or things that don’t make sense (random code snippets, improperly formatted text). Sometimes the text was repeating as well. But I thought that might have been a template problem, because it seemed to be answering the question twice.

Otherwise, all settings are the defaults.

I tried it with both Qwen 14b and Llama 3.1. Both were exl2 quants produced by bartowski.

Perplexica works. It can understand ollama and custom OpenAI providers.

Super useful guide. However after playing around with TabbyAPI, the responses from models quickly become jibberish, usually halfway through or towards the end. I’m using exl2 models off of HuggingFace, with Q4, Q6, and FP16 cache. Any tips? Also, how do I control context length on a per-model basis? max_seq_len in config.json?

Seems to be the only necessary thing in my case! Thanks.

Yeah I definitely have the default GTK chooser. Guess I have some config playing to do later.

Can you explain a bit more about this and how to configure it? When I use FF on gnome, the save dialogue just looks like other dialogues?

Not necessarily. While of course in many many cases, open source is a volunteer effort, there’s usually some implicit transaction going on. Whether that’s improving the software for yourself and passing that on to others, being a business and improving a library or something you use that helps your project generate revenue, or even a straight up commercial transaction.

But in all these cases, the open source project can be taken by you (or others) and you can do whatever you want with it. In the case of Winamp here, you cannot do any of that. It would be different if they were paying for contributions. But they’re not, so.

They basically want free labor.