Viewing profile — eurekin
eurekin
HN member- Joined
- Thu, Sep 06, 2012, 9:39 AM UTC
- HN karma
- 1,030
- Public activity
- 664 items
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About eurekin
Self hosting, SBCs, AI/Vision/LLMs
Recent public activity
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Comment #49253815
Care to share any details? I'm about to check the 2.6b lfm on document editing.
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Comment #49206938
It does? I wonder, what it does to the gut biome then
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Comment #49097625
The needle benchmarks show, that models extended context works for the part, that can be explained as: "I can access/adress that part of the input". I have no idea, why in that con…
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Comment #48977141
I have a feeling this comment will make history
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Comment #48968033
It's a mcp, so connects quite easily to agents. With mcpo, I also connected it to open-webui (which has better support for OpenAI style tools/functions). Used it in claude code wit…
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Comment #48966541
With 3.6 27b, I just stopped changing local models and started tinkering with things on top (like mem0). Feels genuinely useful and more than a toy
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Comment #48944206
Also explains why we like music with two simultaneous distinct sections (bass + the rest). One without the other doesn't feel as complete
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Comment #48796382
Disclaimer, I only use it to grow the "knowledge hub". It's a single git project at my $USER home, that is referenced in global memory. It contains as much information about work t…
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Comment #48794659
That's where the annotation in plannotator helps. I'm asking to scan projects on gitlab, go through some docs to find more grounding material, write a subarticle (in the same style…
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Comment #48793410
Oh, I know exactly what you mean. I use plannotator with claude a lot and have much better time, since I asked for a specific styleguide. I used "CD era MSDN reference and Raymond …
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Comment #48706043
Similarly, I never try to imagine a bright sunshine. It can wake me up
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Comment #48676326
There never are. Those are going to be viewed as two discreet successful interventions. One for lay-offs, because it was the best move at the time with the knowledge they had. Seco…
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Comment #48643504
I remember seeing this popping up in discussions the first time, but never noticed any resolution (other than to train both sides). Has SOTA advanced?
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Comment #48608924
> A shift is happening among major AI labs, who are becoming increasingly skeptical of endless parameter count and training data scaling I'm pretty sure it's mostly due to the trai…
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Comment #48584085
Noticed few cliffs. Sometimes it was a spurious stop (had to write "go on" or "continue" to restart), othertimes it was randomly saying: "Oh the user wants [the thing we already re…
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Comment #48583722
If I started today, with building a server, I'd jump right into verified set-ups and writeups, like this one: https://github.com/noonghunna/club-3090 You can find info about runnin…
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Comment #48582626
> The model is running so hot, that it shoots past the goal and starts looping later: > My latest experiment was setting up vLLM (the gold standard for production and concurrent se…
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Comment #48542088
I'm still sour they had only one toast in, in a two slot toaster
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Comment #48539050
Also, supposedly biggest MMA event Rogan doesn't want to be on. Something is up
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Comment #48525215
I kept getting recipes with "that one ingredient", which was either a major PITA to source or produced too much waste, even from a real world dietician consultation. Example, use 1…
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Comment #48525202
Chrome driven by the OS accessibility API
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Comment #48519023
I keep finding more and more usecases for Q3.6 27b (same league) and the best performance is, when answers to my question is already in the context. The moment I'm trying something…
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Comment #48488619
Yeah, it won't. SWE here with a sidegoal to tackle the deployment side through various means (homelabbing, grabbing sre/cloud/observability tasks at work). The biggest observable i…
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Comment #48322141
It feels now like an alternative timeline, one which performance optimisations were first and foremost still. Sometimes I fantasize, thinking how would our current development ecos…
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Comment #48054404
Batching lowers that, since the model is read once from memory. Activation accumulation doesn't scale as nicely