AxionLab Co.

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Create the best 1M-1B parameters thinking model(All on CPU)

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AxionLab-official

posted an update 3 days ago

Post

8221

Please, give a follow to SupraLabs!

We are researching the most, just to make the best medium models FOR YOU!

SupraLabs/Supra-A2A-Nano-Exp

SupraLabs/Supra-1.5-50M-Instruct-exp

SupraLabs/Supra-50M-Reasoning

SupraLabs/supra-title-50M-pre-gguf

Check more at Supralabs org!

SupraLabs

---
@LH-Tech-AI
@QyrouNnet-AI
@LyJonathan
@Mmorgan-ML
@User01110

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AxionLab-official

posted an update 6 days ago

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3368

# An Open Letter from SupraLabs.

Over the past few days, SupraLabs has been mentioned in a public discussion regarding small language models, scaling laws, and training methodology. We'd like to clarify our position.

Before anything else, we want to make one thing absolutely clear: we have great respect for Lane and the work being done at Glint Research. At no point was our intention to disrespect Lane, Glint Research, or their research. What began as a technical discussion about model scaling and training methodology unfortunately became much more personal than we ever intended. From our perspective, it was simply an exchange of technical opinions, and we sincerely hope it remains that way.
We'd also like to acknowledge that one of our own comments during the discussion was poorly worded. Referring to a benchmark as "fake" was imprecise. What we intended to criticize was the comparison methodology, not the integrity of the evaluation itself. Comparing a merged checkpoint against a single checkpoint is, in our view, not an apples-to-apples comparison.

That said, this was never the core of the discussion.

Our disagreement was not about SLERP, model merging, or whether training a small model on massive amounts of data is an interesting research direction. We support experimentation and unconventional ideas.

The actual point of disagreement was much simpler.

The statement that a 1M parameter model trained on 1 trillion tokens will become a "100M killer" is, today, a prediction, not an experimental result.
Could it happen? Perhaps.
Would it be exciting if it did? Absolutely.

But until benchmark results, reproducible evaluations, and independent validation exist, we believe such statements should be presented as hypotheses rather than established conclusions.
Research advances by testing ideas, not by assuming their outcomes.

We sincerely wish Lane and everyone at Glint Research success in their experiments.

Thank you to everyone who read it.

1 reply

AxionLab-official

posted an update 19 days ago

Post

10924

THIS IS CRAZY! THE MODEL ON THE IMAGE(Supra-50M-Reasoning) answered correctly and its QUANTIZED IN 2BIT! THE RESPONSE IS CORRECT, IN A 15MB SIZE FILE!

14 replies

AxionLab-official

posted an update 21 days ago

Post

6598

We're happy to announce that we released a Reasoning tuned version of Supra-50M!

SupraLabs/Supra-50M-Reasoning

AxionLab-official

posted an update about 1 month ago

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268

Someone ran Supra-50M-Instruct ON A 1GHZ 1999 CPU

https://www.reddit.com/r/LocalLLM/comments/1tm21ar/i_see_your_strix_halo_and_raise_you_a_vintage/

"As a fun experiment, I decided to try running the recently released Supra-50m on a 26-year-old machine I keep for retro Windows 9.X games. Although the model was somewhat silly and inconsistent, the performance wasn't bad, reaching around 1.3 tok/s with CPU inference alone.

Since this CPU doesn't have SSE2, I changed from llama.cpp to llama2.ce and asked Claude to write a custom tokenizer.

It's crazy to think that with the right file size of 200 MB, we could have experienced this magic back in 1999" - u/drone_stonks, r/localllm

AxionLab-official

posted an update about 1 month ago

Post

245

We RELEASED!

SupraLabs just released our 50M model!
Base, Instruct Weights are there, you can use!

You can check blog to more informations!(Writing blog yet!)