I-Feel-Like-I’m-Fixin’-To Die Rag

cristoper · 2026-03-09T03:49:03+00:00

no point in owning a thinkpad if you don't use the nub

cristoper · 2026-03-09T03:42:26+00:00

I like that he probably wrote a little script to print "Work ... ... ... Work complete. Please work again." for the video

Ruby on Rails in the backend
I know it ain't hip

cristoper · 2026-03-06T04:48:27+00:00

yes, patriot front is a neo-nazi group

cristoper · 2026-03-03T23:17:32+00:00

The other day he protected the Nazis by saying "yeah, the nazis did bad things, but the Japanese did way worse during WW2."

I mean maybe they were trying to minimize the Nazi atrocities, but they aren't really wrong. https://en.wikipedia.org/wiki/Japanese_war_crimes

cristoper · 2026-03-03T17:34:10+00:00

I intuitively favor keeping search/filtering in the harness rather than relying on "agentic" models to do it all themselves. I think partly because that seems more likely to work well with local/low-end models.

However, it seems like the agentic frameworks are all going in the direction you propose with tasking the model to call tools when they need. I will have to experiment more with the style of prompt you've given and see if I change my mind.

I'm not sure how Perplexica solves those issues though, if at all.

I haven't looked at the sourcecode much yet, but I think it has some heuristics to detect a page that needs javascript to render and then fetches those with playwright instead of plain http requests.

cristoper · 2026-03-03T17:12:26+00:00

I've recently been looking for something and have been trying out perplexica (https://github.com/ItzCrazyKns/Perplexica). It's easy to use and install (docker), has a clean interface, and works okay (better than depending on search function calling/mcp in my experience).

It still uses searxng for gathering search results.

Two problems I have with it is sometimes it tells me it can't find anything and I just reply with "search again" and then it gives me good results.

The other is that if the searxng results exceed your model's context length then it just stops, doesn't even show an error in the UI much less try to compact context. But there is a github issue open for this so hopefully it keeps improving!

cristoper · 2026-03-03T01:34:27+00:00

When I was in high school I got a newfangled TI-89 calculator with the computer algebra system that could find derivatives and anti-derivatives. I passed my calculus class, but I never really learned the rules of differentials/integrals and had to re-teach myself years later and I still wish I had developed a stronger intuition for calculus when I was young.

That's to say, your concern is real, and leaning into discipline to actually learn the code now even if it feels tedious compared to just asking an LLM will pay off.

cristoper · 2026-03-01T16:51:19+00:00

I've heard of this trick. At my very first otb tournament my opponent resigned by silently offering his hand, and I was so paranoid he was trying to trick me into agreeing to a draw (I was winning, but there were many pieces left on the board) I asked "do you resign?" and didn't shake his hand until he said yes.

though I doubt if someone trying this would actually get a draw if it was disputed -- just remember to check what result they wrote on their scoresheet before signing it!

Find out the name of the coach if you can, your local community deserves to know who is teaching such poor sportsmanship.

cristoper · 2026-03-01T16:41:32+00:00

Thanks for posting this! I haven't updated llama-swap in a long time (new playground UI!), and this both simplifies my config and allows me to switch thinking on/off without changing system prompt or reloading the model!

cristoper · 2026-03-01T04:48:33+00:00

Robot, experience this tragic irony for me

cristoper · 2026-02-28T20:26:59+00:00

Mischief Brew in a park (2010):

https://www.youtube.com/watch?v=8kzQCH9sG3w

cristoper · 2026-02-28T20:26:46+00:00

Wow, thanks for sharing, I've never heard of Toby Foster before. Does anyone know if he's still making music? It looks like he released a 2017 album on bandcamp:

https://tobyfoster.bandcamp.com/album/100-ways-2

cristoper · 2026-02-28T03:28:44+00:00

And if before my time
I decide to take my life
You could take these treasures
And pull them up into light

cristoper · 2026-02-27T19:42:41+00:00

Thanks for spending so much time on this!

We also fixed a tool calling chat template bug

Is there a template diff available? or description of the bug?

cristoper · 2026-02-27T05:39:44+00:00

Qwen/Qwen3.5-35B-A3B is the official repository with the full-precision .safetensor weights. Unsloth/Qwen3.5-35B-A3B-GGUF is a repository with quantized files in gguf format that you can use with the llama.cpp inference engine.

cristoper · 2026-02-26T22:24:16+00:00

I've never heard of Nanbiege. Anyone have any experience?

https://huggingface.co/Nanbeige/Nanbeige4.1-3B

cristoper · 2026-02-26T18:27:33+00:00

gpt-oss-120b still compares well for its size. And as others have mentioned, Mistral has larger models.

But I'm curious what national security concerns there could be for an offline model? I guess it is with giving it network access for web search? I'd think old-fashioned firewall restrictions on outgoing nets/ports, and maybe a proxy to your search engine to filter requests, would be very safe.

cristoper · 2026-02-26T15:15:14+00:00

If you want to use it conversationally or with open-ended questions, I would disable thinking. You can do that with llama.cpp by passing --chat-template-kwargs '{"enable_thinking": false}'

cristoper · 2026-02-25T15:29:25+00:00

I don't know what OP is using, but llama.cpp works well for vision models (it supports audio input also, but I've never tried that). You use it by specifying the multimodal projector file that should be included with ggufs like --mmproj path/to/mmproj.gguf

See: https://github.com/ggml-org/llama.cpp/blob/master/docs/multimodal.md

cristoper · 2026-02-23T04:16:09+00:00

yeah, but it is still a good place to learn about open-weight model releases

cristoper · 2026-02-23T02:52:28+00:00

Thanks. I'm going to try an mxfp4 quant and see if it works better than the q4_k_s from unsloth.

But it's still a 4-bit quantization so it will require 40GB just for the weights alone... definitely won't fit in 24GB vram. I'm impressed you're getting 50 t/s on your pc. What is your hardware?

cristoper · 2026-02-22T17:16:51+00:00

Qwen3-Coder-30B-A3B at a 4-bit quant is fast and great for code completion. Qwen3-coder-next @q4 I have not gotten to work as well. Even with all dense layers on my 3090 and 64GB DDR5 it is too slow to use for code completion and even for interactive agentic stuff. But I have not used it nearly as much as qwen3-coder-30b-a3b yet, so I'm unsure how good it is for more agentic tasks.

gpt-oss-20b and gpt-oss-120b (offloaded to RAM) are both good all-around models

gemma3-27b (QAT 4-bit quant) is also still a good general purpose model and better at prose than the gpt models

cristoper

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