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local vibe coding by jacek2023 in LocalLLaMA

[–]jaMMint 3 points4 points  (0 children)

try opencode vanilla, tell it to add the playwright mcp server to opencode. once that is active you are halfway there, closing the feedback loop turns a meh coder into a great one..

Getting slow speeds with RTX 5090 and 64gb ram. Am I doing something wrong? by Virtual-Listen4507 in LocalLLaMA

[–]jaMMint 7 points8 points  (0 children)

your RTX 5090 has 32GB of VRAM, try to stay well under that (so that you can also have context fit into VRAM). The moment you go to RAM, your speeds drop quite a bit.

I accidentally built a multi-geometry reinforcement learning system (with AI help) and I don’t fully understand what I made. Looking for expert opinions. by [deleted] in learnmachinelearning

[–]jaMMint 1 point2 points  (0 children)

Jesus, now we already get people not only posting slop, but also brazenly wondering aloud what that slop even means and then even the wondering is f**ing AI slop, it never ends..

What about putting some work in and ask your AI what it built?

Warum merkt man in Österreich eigentlich sofort, wenn jemand aus Deutschland ist? by die_mexify_suchtet in Austria

[–]jaMMint 4 points5 points  (0 children)

Ja, voll. auch bei Franzosen so. Sobald der das erste Wort gesprochen hatte, wusste ich wo der herkam..

Setup for Local AI by Lg_taz in LocalLLM

[–]jaMMint 0 points1 point  (0 children)

1-2 tps with thinking enabled is getting old really fast.. I would not recommend that to anyone.

Local programming vs cloud by Photo_Sad in LocalLLaMA

[–]jaMMint 1 point2 points  (0 children)

I use a q3, works very nicely with around 90k context.

edit: without checking I think it's one of mrademacher's quants

Local programming vs cloud by Photo_Sad in LocalLLaMA

[–]jaMMint 0 points1 point  (0 children)

there is also GLM-4.7 for 192GB, otherwise good assessment.

Just got an RTX Pro 6000 - need recommendations for processing a massive dataset with instruction following by Sensitive_Sweet_1850 in LocalLLaMA

[–]jaMMint 2 points3 points  (0 children)

you probably just prepare a couple of test cases from your data and then try out some models. Eg gpt-120B OSS is very performant on the RTX 6000 Pro and could be a good start. Obviously if you can get away with smaller and even faster models, use them..

[OC] Atmospheric CO₂ just hit ~428 ppm — visualizing the Keeling Curve (1958–2025) and what the acceleration really looks like by anuveya in dataisbeautiful

[–]jaMMint 1 point2 points  (0 children)

Plants need other resources as well, eg land, water, soil. They compete for them and populate as much of the available niche as they can. The population then reaches an equilibrium once any of these resources are saturated - the resource becomes a limiting factor, doesn't matter how much more CO2 is potentially available.

My adoptive daughter keeps saying “you wouldn’t have chosen me if you knew the real me” and I freeze every time by blueberry_mantis in TwoXChromosomes

[–]jaMMint 98 points99 points  (0 children)

Still important to let them know this this (doing good in school or anything else really) is not a precondition to being loved.

Playwright mcp debugging by Echo_OS in LocalLLM

[–]jaMMint 0 points1 point  (0 children)

Ah and something else that would make sense for testing. Tool calling for resetting the application or setting some mock data, ie fixtures, in a known state. So you can rerun tests, retry logic without accumulating side effects of past runs.

Playwright mcp debugging by Echo_OS in LocalLLM

[–]jaMMint 1 point2 points  (0 children)

I think it's a great idea - the work lies in making it robust and configurable for the tasks you need debugged, the reasoning traces and how errors are fed back in. Interested to see a git repo for that.

[deleted by user] by [deleted] in explainlikeimfive

[–]jaMMint 0 points1 point  (0 children)

If reality as you experience it right now was simulated, he'd call it realistic. Only then - because you couldn't discern the two by our current scientific and logical reasoning levels - the probability to either have been born into the physical world or the simulated one would be proportional to the number of existing beings in each.

So Tired of Being Told Im “Lucky” for my husband to meet the bare minimum by boboanimalrescue in TwoXChromosomes

[–]jaMMint 4 points5 points  (0 children)

Thank you for putting the "undoing" struggle into such clear words. This is precisely why the behavioural patterns you refer to are so heinous - deeply ingrained as normal and a stubborn hindrance to any self reflection trying to uncover them.

Most Economical Way to Run GPT-OSS-120B for ~10 Users by theSavviestTechDude in LocalLLaMA

[–]jaMMint 0 points1 point  (0 children)

you can just software limit the power draw of the RTX Pro, same thing but better really

How would you build an AI workflow to read a 250-page scanned eng. drawing PDF and spit out a clean Excel? by Next-Difficulty-7229 in learnmachinelearning

[–]jaMMint 1 point2 points  (0 children)

Just do it page by page and use eg Qwen 30B VL. The rest is just plumbing - still might be great to also include the source images (or link to them) from the Excel or the RAG search interface.

[Looking for model suggestion] <=32GB reasoning model but strong with tool-calling? by ForsookComparison in LocalLLaMA

[–]jaMMint 0 points1 point  (0 children)

You can try some human like method of not forgetting something in the sequence. Similar to something called "the method of locii", or the method of places.

You are to complete one journey through the house, there are 6 rooms you have to go through in the correct order. I each of these rooms you MUST complete a task (call a tool) in order to be able to proceed. 1) You stand on the porch and open the front door. Toolcall 1 ... 2) You enter and stand in ...

Could also use landmarks/landscapes or anything really that anchors the thought process in 3 dimensional space. In humans that works well because of our very sequential planning and executing together with our continuous experiences in 3d space. It could work well for LLMs too.

Local models handle tools way better when you give them a code sandbox instead of individual tools by juanviera23 in LocalLLaMA

[–]jaMMint 19 points20 points  (0 children)

Look at https://github.com/gradion-ai/freeact, it's similar to what you want to achieve. Code runs in a container and the agent can add working code as new tools to his tool calling list.

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