SupraLabs

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AxionLab-officialย  published a model about 9 hours ago
SupraLabs/SupraIMG-0.7
AxionLab-officialย  updated a model about 9 hours ago
SupraLabs/SupraIMG-0.7
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LH-Tech-AIย 
in SupraLabs/SupraSafety-18M about 4 hours ago
QyrouNnet-AIย 
in SupraLabs/SupraSafety-18M-Demo about 16 hours ago

test

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#2 opened about 16 hours ago by
catixInc
AxionLab-officialย 
posted an update 1 day ago
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4146
โš ๏ธ Community Notice

We would like to clarify that SupraLabs has no affiliation, partnership, or connection whatsoever with "SupraLarps" or its members.

Please avoid interacting with their organization, repositories, or Spaces under the assumption that they are associated with us.

We are currently aware of the situation and have already contacted the appropriate channels to address it.

Thank you to everyone who continues to support SupraLabs. โค๏ธ
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MoE?

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#1 opened 4 days ago by
catixInc
AxionLab-officialย 
posted an update 9 days ago
AxionLab-officialย 
posted an update 11 days ago
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3400
# 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.
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AxionLab-officialย 
posted an update 24 days ago
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10964
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!
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AxionLab-officialย 
posted an update 27 days ago
AxionLab-officialย 
posted an update about 1 month ago
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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-officialย 
posted an update about 1 month ago
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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!)
  • 2 replies
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