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AtAndDevย 
posted an update about 6 hours ago
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@Banaxi-Tech stop hiding my comments. AND STOP STEALING PAPERS AND SPREADING MISINFORMATION.
your BGA blog is a copy of NSA (deepseek, 2025) branded under your name. literally the same top16 selected blocks, 512 local window, router over block summaries, all you did was change block size from 64 to 128.
you didnt cite NSA once but you put a โ€œplease cite BGAโ€ bibtex at the bottom.
i commented under your post and said that there is no way that you can support claims like: โ€œThe Accuracy Should BE WAy better than DSA but untested yet.โ€ you didnt run a single experiment. and the 256x isnt from BGA, its just n/2k with k=2048 so the exact same k DSA uses. if opus wrote this for you, at least read it before posting.
i commented again after you hid my comment despite it having constructive and correct feedback and you hid that too. and again.
you can hide the truth and just try to get hf post likes..... but is it really the thing that needs to be done? do you really want to take papers and make them yours while barely even changing the params?

admitting your mistakes and doing something about them needs humbleness, intelligence, humanness.
i encourage you to admit your mistakes and try to do better next time (at least read what blog your ai wrote or do proper experiments to back your stuff up).
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ProCreationsย 
posted an update 15 days ago
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auto 200m 2 is out now!
Auto is a series of models designed to classify if a tool called by an AI agent is safe to run or not, like how the "auto" approval modes work in codex or claude. This is the smallest model in the series by far and it still packs a punch! Over 96 percent accuracy on the held out benchmark, beating deepseek v4 0731 and absolutely destroying regex at classifying if a tool call is safe to run (to be fair it is a bit of a weird and very hard benchmark but it works!)
check it out: ProCreations/auto-200m-2
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ProCreationsย 
posted an update 21 days ago
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Introducing Bonsai 2 27b GSQ RCO! It applies two newly-popular methods for quants to retain higher accuracy. Bonsai 2 27b GSQ RCO achieves around 6 percent lower perplexity on WikiText-2 compared to Bonsai 2 27b and roughly unchanged benchmark accuracy overall, with small mixed differences. It stays under 7gb, staying small like the original bonsai. Note that this is more of an experiment than a true finished product but the gains we saw are cool! Test it out and let me know what you think!
ProCreations/bonsai-2-27b-gsq-rco-gguf
ProCreationsย 
posted an update 23 days ago
ProCreationsย 
posted an update 26 days ago
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ICYMI:
Grug 27b v2 released! It brings increased quality, fixes repetitive loop / malformed session title issues seen in grug 27b v1.1, and reasoning efforts now truly work.
ProCreations/grug-27b-v2
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ProCreationsย 
posted an update 28 days ago
ProCreationsย 
posted an update about 1 month ago
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Grug 27b gguf got around 400,000 downloads. Grug v1.1 gguf got around 1000. Do you guys want new grugs?
ProCreationsย 
posted an update about 1 month ago
ProCreationsย 
posted an update about 1 month ago
ProCreationsย 
posted an update about 1 month ago
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nvidia
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AtAndDevย 
posted an update about 1 month ago
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SPECK 2 IS ALREADY OUT: specklabs/Speck2-140M

Pretrained on 4x more tokens than the previous releases (20b vs 5b).
Instruct tuned versions are coming soon.
Very interesting models are coming soon too (hint: super long context).

Thanks for everyone supporting!
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ProCreationsย 
posted an update about 1 month ago
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2151
what should i make next?
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AtAndDevย 
posted an update about 1 month ago
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SPECK1.5 IS COMING SOON!
Same 5B token budget but much better corpus quality.

Also getting a ton of downloads, thanks for everyone downloading and liking <3

specklabs
ProCreationsย 
posted an update about 1 month ago
AtAndDevย 
posted an update about 2 months ago
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NEW SPECK UPDATES:

Just hit #14 and #15 with out FIRST models on Open SLM Leaderboard. The models were trained on 5B tokens, while competing with similarly sized models trained on more than 6-20x the data.

A new base model Speck1.5-140M being trained right now on a higher quality corpus and will be released soon.
SpeckChat3 is coming very soon with 1 million samples, specifically designed to post train small base models.

Also, just to clarify stuff, we will NOT release anything that is NOT MIT licensed EVER. Openness is needed in small language research.

Thanks to everyone supporting the project, and stay tuned for new releases!