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AxionLab

AxionLab-official

87 38 304

AI & ML interests

Owner of SupraLabs and iGPU Lover

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liked a Space about 21 hours ago

LizardModels/SLM-Leaderboard

liked a model 1 day ago

TobiasLogic/chessmamba

new activity 1 day ago

AxiomicLabs/Open_SLM_Leaderboard:Can you add SupraElegans-500k please?

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reacted to appvoid's post with 🔥 2 days ago

Post

2321

I don't know if it was us or one of you guys or maybe all of us at once but lately we have seen a finetuning/pretraining explosion of models below 200m params and we can't be more happy about it keep coming tinkerers all of this is possible because of you!

8 replies

replied to Enderchef's post 6 days ago

Supra2 100M, BananaMind 2 Pro and GPT-X2.5-135M all releasing at the same time is exciting!

We might going to make Supra2-1B, MAYBE

reacted to Enderchef's post with 🤗❤️🚀🔥 7 days ago

Post

3406

🚀 Supra2 100M is out, and multiple other SLM orgs are gaining power!
Following takes a press. Please follow:

fromziro

SupraLabs

AxiomicLabs

8 replies

replied to LH-Tech-AI's post 7 days ago

https://huggingface.co/spaces/AxionLab-official/Supra2-100M-Instruct-Demo

reacted to LH-Tech-AI's post with 🤯🚀🔥 7 days ago

Post

3416

Supra2-100M is out!
Go check it out:
- https://www.reddit.com/r/LocalLLaMA/comments/1velyl9/new_models_supra2100m_base_and_instruct_go_check/
- https://huggingface.co/SupraLabs/Supra2-100M
- SupraLabs/Supra2-100M-Instruct

Give us a like and a follow!!

HAVE FUN 🤗🔥🚀
more coming soon...

1 reply

reacted to their post with 🔥 8 days ago

Post

3448

Tommorow we are releasing Supra2-Pro(100M params), our flagship, get ready!

(follow SupraLabs to get tuned in!)

SupraLabs

9 replies

posted an update 8 days ago

Post

3448

Tommorow we are releasing Supra2-Pro(100M params), our flagship, get ready!

(follow SupraLabs to get tuned in!)

SupraLabs

9 replies

reacted to LH-Tech-AI's post with ❤️ 9 days ago

Post

2391

Announcing The Supra2 Family And Supra2-100M

Today, we are announcing a brand-new series of SupraLabs models: Supra2
This series will feature various models, including such as:
- 🐜 Supra2-Nano (0.4M) → The smallest Supra2 model.
- 🤏 Supra2-Small (1.4M) → The tiny model that runs everywhere.
- 💪 Supra2-Medium (25M) → Our medium class model in the Supra2 family. The powerful midsizer.
- 🔥 Supra2-Pro (100M): base, instruct, reasoning, code, math and more! → The most capable model yet! A real allrounder for all your everyday tasks.
- 🎨 Supra2-IMG → our generative text-to-image model
...and many more...

Current progress:
- Nano (0.4M) and Small (1.4M): in training; almost done. Baseline set.
- Medium (25M): coming soon...
- Pro (100M): in training; finishes in 66 hours - Monday, 3rd August 2026, 12:00AM
- IMG: coming soon...

You can support us with a like and follow if you want!
Don't miss our next release! Stay tuned...

30 replies

reacted to their post with 🧠👀🔥 9 days ago

Post

11065

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!

15 replies

reacted to OppaAI's post with 😔 9 days ago

Post

1079

After a month of interacting with my AI Waifu, I noticed a few issues in the system; so I decided to spend this week revisiting the systems implemented in Phase 1.0, 1.5 and 2.0, and try to make them to be more like production-grade as much as possible:

1) Memory Degradation - recalled memories are not as good as in the beginning, causing AI Waifu to be more chaotic as she hallucinates over contaminated memories like a bad vicious cycle.
So I transformed the original stateless sqlite-vec vector store to be a simple entity co-mention graph. And even make a studio to visualize the memories stored inside the vector db.

Just by looking at the graph, I saw a couple issues:
a) After 1.5 months of interactions, there should be only one month of pinned memory (in green) over 1.5 months of active memory (in purple). How come pinned memory is in majority over active ones?
I suppose the forgetting curve I had set too aggressive and memory half-life and shelf life too short, active memory got decayed way before monthly consolidation and got lost forever.
b) I saw she memorized me into 3 different entities: my username, my nickname and my Github user ID (leaked into pinned memory, presumbly during nightly dreaming process). 3B small param LLM has hard time to correlation 3 different entities into single person, I may have to harden into one.

2) RAM burst during voice input - for some reason the tensor calculation of SileroVAD of the voice input uses PyTorch, and that's the only place in the whole codebase using torch after removing it from TTS synthesization. By switching to SileroVAD-onnx integrated in the ASR sherpa-onnx, the RAM usage drops at least 0.5GB (after shaving off ~1GB from TTS) by completely remove PyTorch dependencies.

3) Introduced a better Wake Word system using Livekit-Wake word instead of using ASR to do the wake word activation to save computation. Optional features like Speak Verification, Barge-in sensitivity, etc, need to find the optimum settings.

reacted to Enderchef's post with 🧠🤝🔥 10 days ago

Post

2367

I've left Glint Research.
After a long time in Glint Research, an entire distributed training grid built free for them, and more, I've decided that I no longer want to be affiliated with Glint Research.
More updates will follow. Comments/questions are welcome.

While you're reading this, follow these orgs! Following takes just a few seconds, and can change someone's day.

AxiomicLabs

fromziro

SupraLabs

2 replies

AxionLab

AI & ML interests

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