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sleepyeldrazi

HN member
Joined
Thu, Jun 03, 2021, 1:02 PM UTC
HN karma
85
Public activity
29 items

About sleepyeldrazi

Personal projects at https://git.kokoham.com/sleepy . Trying to optimize LLM inference frameworks for local models in speed, and explore interesting quants for size.

Recent public activity

  1. comment
    Comment #48730373

    I got it off kleinanzeigen, its a ebay-like site (but mostly 'pick it up yourself' instead of delivery). Looking at it right now, i do see multiple sales for 850-900. I did spot th…

  2. comment
    Comment #48723391

    I can't speak for the US, but in Germany (where hardware is usually more expensive, not less), I got my 3090 3 months ago for 750 euro and have been running the iq4_nl 27B using q4…

  3. comment
    Comment #48722487

    I need to ask, since I have desperately wanted to make Gemma 4 12B work, but im not sure if its the quant (i usually up it to q8, which is a lot higher than iq4_nl that i use for 3…

  4. comment
    Comment #48722391

    I've been running it almost since launch on a 3090 (24gb vram), you really don't need that much. Second hand those are really cheap and i get 50-70 t/s (with MTP at 2), full ctx. I…

  5. comment
    Comment #48635330

    Inspired by [ https://github.com/antirez/ds4 ](ds4), [ https://github.com/CerebrasResearch/reap ](REAP) and [ https://huggingface.co/0xSero/DeepSeek-V4-Flash-162B ](OxSero's Deepse…

  6. story
  7. comment
    Comment #48625438

    That's why I like qwen3.6 27B, it has 0 ego, it knows that it doesn't have complete world knowledge, so when it sees a web_search tool it searches all the time. Even qwen3.5 9B is …

  8. comment
    Comment #48583979

    Opus also has a deeply ingrained personality that always de-rails sneakily into what it's taught, not what the user intends. This is good if the user doesn't know the details of th…

  9. comment
    Comment #48354691

    Have you tested Qwen3.6 35B? Putting aside the capability claims for that model (which I support, but are not my point here), that 35B has smaller active parameter count than the g…

  10. story
    Ask HN: Local model experiences with 'high-reasoning distill' finetunes

    What are your experiences with all the different variations of finetunes on small models ( I have seen them perform better on public benchmarks in some cases, which shouldn't be ig…

  11. comment
    Comment #48183271

    Finetuning takes little resources, the base model training is the slow and expensive part. Architecturally 3.5 models are identical to their 3.6 counterparts, that is why there is …

  12. comment
    Comment #48183222

    The best thing I have come up with is just make a bunch of prompts / tasks that I personally care about and need a model to know how to do. As an example, when qwen3.6 27B dropped,…

  13. comment
    Comment #48182673

    I don't think I can handle another small model release by qwen, I'm still trying to find the limits of 3.6 27B and they are already threatening us with a new one? But jokes aside, …

  14. comment
    Comment #48171633

    I feel like if I had the infrastructure and saw that there is a huge interest in the model, i'd just undercut alibaba's prices a little harder to grab all the consumers. I am sure …

  15. comment
    Comment #48169097

    If you want a good dense model, use qwen3.6 27B instead, speed will be up, and if you don't take my word for it being smarter, take openrouter's prices of it against the bigger, sl…

  16. comment
    Comment #48163285

    It is actually very exciting that they are also working on 3.5, I will keep this toy project up in the meantime, trying it out and testing things around it helps me learn a bunch. …

  17. comment
    Comment #48162718

    Think of this as another way of achieving that. This theoretically has a higher ceiling of how much it can predict at a time. And more importantly is a lot more memory efficient du…

  18. comment
    Comment #48162374

    If anyone is interested in watching my 0.8B experiments: https://orthrus.kokoham.com/ . The current code is here: https://git.kokoham.com/sleepy/qwen_orthrus . The hard part was th…

  19. comment
    Comment #48158461

    My plan is to validate it first using qwen3.5 0.8B if it even works (as it has the same architecture as qwen3.6 27b, just scaled down a bit) on my 3090. If it does, I'll make a git…

  20. comment
    Comment #48157766

    Scratch that, I don't have that kind of money, and 3.5's architecture is a little more divergent from 3's, so it will be a bit less trivial. It does look possible, just not on a st…

  21. comment
    Comment #48157655

    From a quick and shallow view of the paper, it looks very feasible (with a little tinkering ) to be adapted to qwen3.6 27B. The process looks somewhat similar to training a LoRA, o…

  22. comment
    Comment #48147095

    I love this community, I started building a simple website for this exactly a couple of hours ago and you made an even more advanced version already. Hats off to you sir. If i ever…

  23. comment
    Comment #47931445

    I specifically tested on tasks I designed because I know every modern model, not only local ones, are bechmaxxed. The common benchmarks most labs use are (very likely) in their dat…

  24. comment
    Comment #47927421

    I haven't honestly dug around to figure out if there's a hardware reason for it, but prompt processing has always been a lot slower for me on macs in general. I mostly use MLX on m…

  25. comment
    Comment #47924352

    I have been testing and using Qwen3.6 27B (running from my 3090) since it dropped and I genuinely think this is the first consumer hardware-grade model that can actually replace fr…