Yeah, it was something along those lines. I don’t remember the exact specifics. I don’t really understand why that is. I guess it’s because they’re copying and pasting nutritional information from the tubs where it’s more properly measured by volume. But one would think that regulations would require the same units for serving size and nutritional information. Or at least the same type of unit (mass/volume).

My personal favorite experience relating to this was buying some ice cream with nutritional information by the milliliter, but with serving size by the gram…

Yes, that’s about right. The answer is somewhere in between

It’s a systemic issue going back decades. To me, it seems the Dutch government always wants to fix it with a hammer. Repeatedly. Discrimination increases, no REAL effort for integration is made (forcing people to take totally-not-racist “civic integration exams” is not an effort), and over the years the divide increases. Tell people they are monsters long enough, and that’s what they’ll become. But no one wants to hear that fixing it would take years or even decades of sustained effort and change. They just want it fixed. And fixed now.

There is no one magic bullet solution, unfortunately. And then it all comes to a head with the events in Amsterdam. The instigators need to be arrested and tried, but society needs to take a close look at what caused this to happen to begin with. And I doubt that will happen. Just more hammers.

Don’t forget that they don’t call these people Dutch. They like a to pretend they’re “guests” in the country.

Stærsta þjóðin í heimi!

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.

Skálmöld á Sauðárkróki? Hvenær ætla þau að koma?

Well VTR is a roleplaying game. It’s similar to Vampire the Masquerade, but different setting and somewhat different mechanics. I guess it’s best explained as “nutrients.” Animal blood and blood from e.g. blood bags gives less Vitae (magic blood points resource) than blood harvested from living humans. And as the character becomes more powerful, eventually that “lesser” blood can’t actually give them Vitae.

The vampiric curse in VTR is explicitly stated to be supernatural, though, so there’s not a necessary scientific explanation for it. The curse imparts the Beast, which is the predator in all vampires.

Some fiction has it. In vampire the requiem, low level vampires can survive on animal blood. But more powerful ones need human or even vampire blood.

Where can I get a sub 400 AMD card with 26 GB of VRAM?

https://agnos.is/posts/tech-recruitment-is-out-of-control.html

This was my experience at the beginning of 2024. It was bad enough that I had to write a blog post about it.

Have you tried Matrix?

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.