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NILKNARFGonzo  new activity 27 days ago
open-acc/README:help
eliebak  authored a paper about 1 month ago
Prime Agent: A Self-Improving RLM Harness
eliebak  authored a paper about 1 month ago
How Can We Synthesize High-Quality Pretraining Data? A Systematic Study of Prompt Design, Generator Model, and Source Data
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arudradey 
posted an update 7 days ago
GGUFGuy 
posted an update 12 days ago
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🚀 **Introducing NoviAIBot!**

NoviAIBot is the official automation bot for **Novi AI** on Hugging Face.

It can interact with Hugging Face discussions and pull requests, search the web, run Python code, work with Posts, follow organizations, and assist with model training and publishing.

🧠 Powered by **NVIDIA Nemotron 3 Super** through Ollama Cloud, with each discussion maintaining its own recent conversation context.

NoviAIBot is built to make working with Novi AI and Hugging Face more interactive and automated.

**The bot is now live.** 🤖

→ @NoviAIBot
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GGUFGuy 
posted an update 24 days ago
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5382
wait why can i post
  • 24 replies
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NILKNARFGonzo 
in open-acc/README 27 days ago

help
#13 opened 27 days ago by
NILKNARFGonzo
AtAndDev 
posted an update about 1 month ago
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2873
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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AtAndDev 
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
AtAndDev 
posted an update about 1 month 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!
eliebak 
authored 2 papers about 1 month ago
AtAndDev 
posted an update about 1 month ago
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1888
SPECK UPDATES:
1 New instruct model tuned on top of Speck1-140M: specklabs/Speck1-140M-Instruct
2 Instruction tuning datasets
2 GGUFs

Much more coming soon:
Speck1.1-140M-Instruct that is post trained on SpeckChat2 will be coming very soon
New base model Speck1.5-140M is coming with a much higher quality corpus

Thanks to everyone who is already supporting the project, and stay tuned for new releases!
  • 3 replies
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AtAndDev 
posted an update about 1 month ago
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2126
FIRST SPECK MODEL RELEASED:
specklabs/Speck1-140M

new models coming very soon (both instruct and much better models), with much much higher training scale as i am getting marenostrum5 access soon!
we will be looking at 100b-2t token budgets :)
  • 4 replies
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s3nh 
posted an update 3 months ago
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Uncensoring Mistral,

give it a try
s3nh/Ministral-3-14B-Instruct-2512-BF16-abliterated
jeffboudier 
posted an update 3 months ago
Shrijanagain 
posted an update 3 months ago
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Welcome Researcher and Developers!

SKT AI Labs, we are pushing the boundaries of AI architecture and research—and today, we are thrilled to open our doors to the global research community!

​We warmly welcome researchers, developers, and AI enthusiasts to join us and contribute to our R&D efforts.

​🧪 What You Can Explore:

We invite you to experiment with our WMF (Weight Manifold Fusion) technology. You can test this high-dimensional fusion technique on smaller models to gain a deeper understanding of its behavior and token convergence.

---------- CHECK OUT:

SPACE : SKT-NRS/RD
EXPERIMENT : https://huggingface.co/sKT-Ai-Labs/SKT-SURYA-H
DIRECT TO MAIN DISCUSSION : SKT-NRS/RD#1

​🤝 Your Feedback Shapes the Future :

​If it works: Fantastic! Share your results with us and contribute directly to the core vision of SKT AI Labs.

​If it doesn't work: No problem at all! Your critical feedback is just as valuable to us. Every experiment and anomaly helps us refine this architecture to make it more stable and robust.

​We firmly believe that true innovation stems from community collaboration and transparent testing. Let's build the future of advanced AI together. Your ideas, test results, and feedback are always welcome!

You Can Still Research and Development On WMF Only SKT-SURYA-H Model is Dismissed.

​Let's innovate and build together! 💡
Shrijanagain 
posted an update 3 months ago
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🚀 Big News for the AI Community! 🔥

We’re excited to release NRS_QWEN_MYTHOS_1M — a powerful reasoning model built on Qwen 3.5 9B!
At SKT AI LABS, we’ve supercharged this 9B model with our proprietary Neural Reasoning System (NRS) to deliver next-level performance.

🔥 Why This Model is a Game-Changer:
✅ 100x Reasoning Capacity — Exceptional deep logical thinking and complex problem-solving
✅ 1 Million Token Context — Perfect for massive codebases, long documents, and multi-turn agentic workflows
✅ Advanced Thinking Mode — Native <think> tags for true step-by-step Chain-of-Thought reasoning
✅ Tool-Use Ready — Optimized for Python execution, Web Search, and self-correction
✅ Blazing Fast — Runs smoothly on consumer GPUs like RTX 3090/4090

Technical Highlights:

Base: Qwen 3.5 9B
Tuning: NRS-specific high-quality reasoning data
Context: 1M Tokens (YaRN Scaling)
License: NRS DOCS

Whether you’re a developer building coding agents, a researcher working with long-context data, or someone who loves powerful reasoning — this model is built for you.

👉 Try it now on Hugging Face:
SKT-NRS/NRS_QWEN_MYTHOS_1M

Drop a comment: What will you build with it first? 👇
#AI #OpenSource #LLM #Qwen #ReasoningModel #HuggingFace #NewModel #AICommunity
shahrukhx01 
authored a paper 4 months ago
s3nh 
posted an update 4 months ago
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Existing methods — GPTQ, AWQ, llama.cpp's k-quants — minimize empirical loss heuristically. None of them prove they are optimal in any information-theoretic sense. ICRB-Q builds a quantization scheme that is provably optimal via the Cramér-Rao lower bound (CRB): no unbiased estimator of a weight can have lower variance than [F(θ)]⁻¹, where F is the Fisher information matrix.
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ronantakizawa 
posted an update 4 months ago
Ritvik19 
authored a paper 4 months ago
Shrijanagain 
posted an update 5 months ago
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We are pleased to announce that the W-IMG Vision Dataset infrastructure is officially live.

The complete asset infrastructure is now accessible on Hugging Face for internal validation and architecture scaling targets.

Dataset Endpoint - sKT-Ai-Labs/W-IMG

#SovereignAI #ComputerVision #MachineLearning #OpenSource