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ST-x-Tony 
posted an update 1 day ago
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Hello AI Community! 👋

We are thrilled to announce the release of **NRS_QWEN_MYTHOS_1M**, a high-performance reasoning model built on the powerful **Qwen 3.5 9B** base. At **SKT AI LABS**, we’ve applied our proprietary **Neural Reasoning System (NRS)** to push the boundaries of what a 9B model can do.

🔥 **Why this model is a Game-Changer:**

✅ **100x High Reasoning Capacity:** Deep logical thinking and complex problem-solving via NRS Boosting.
✅ **1 Million Token Context:** Handle massive codebases, long documents, and multi-turn agentic tasks with ease (YaRN Scaling).
✅ **Advanced Thinking Mode:** Native tags for step-by-step Chain-of-Thought reasoning.
✅ **Tool-Use Ready:** Optimized for Python execution and Web Search with self-correction.
✅ **Blazing Fast:** Efficient 9B architecture that runs smoothly on consumer hardware (RTX 3090/4090).

🛠️ **Technical Highlights:**
* **Base:** Qwen 3.5 9B
* **Tuning:** NRS Specific Tuning high-quality samples.
* **License:** NRS DOCS
Whether you are a developer building coding agents, a researcher dealing with long-context data, or just someone who loves deep reasoning, this model is built for you.

👇 **Try it now on Hugging Face:**
SKT-NRS/NRS_QWEN_MYTHOS_1M
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ST-x-Tony 
posted an update 4 days ago
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Hello everyone,

We are excited to share that SKT-NRS is now live on Hugging Face.
We’ve developed a Neural Reasoning System (NRS) designed to enhance the capabilities of foundation models — giving them stronger reasoning, improved performance, and more reliable outputs across a wide range of tasks.

Our goal is to bring meaningful quality improvements to both new and existing models. You’ll start seeing boosted versions of various models released here soon, each refined with our NRS approach.

**What to Expect* ❤️‍🩹

Regular releases of Neural Reasoning-enhanced models
Clear focus on better reasoning and overall model quality
Ongoing improvements based on community feedback

If you’d like to stay updated, feel free to follow this space — we’ll be posting the first boosted models very soon.

**Community Requests**

Have a specific model you’d like us to work on? Looking for improvements on an existing model, or have any other requests?
We’re happy to hear from you. Please share your suggestions here:

## Community Requests → SKT-NRS/README#1

**Thank you for your support! We look forward to building better models together.**
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oncody 
posted an update 3 months ago
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Are Large Language Models actually becoming more intelligent, or just better at seeming intelligent?

There is a noticeable shift happening in the LLM space.

Models today can:

Generate cleaner and more structured code.
Explain complex topics in simpler ways.
Maintain longer and more coherent conversations.

Yet at the same time, they still:

Produce confident hallucinations.
Fail in multi-step reasoning tasks.
Break under slightly unfamiliar or challenging inputs.

This raises a critical question.

Are we advancing intelligence, or optimizing presentation?

Most improvements so far seem driven by:

Larger datasets.
Increased scale.
Alignment techniques like RLHF.

But these do not necessarily lead to genuine reasoning ability.

What still appears fundamentally missing:

Persistent memory across interactions.
True reasoning rather than pattern completion.
Grounded understanding connected to real-world context.

Reliable self-correction and verification mechanisms.

If current scaling trends start to plateau, the next breakthrough will not come from doing more of the same.

So the real question for the community is:

If you were designing the next generation of AI systems, where would you focus?

A. Larger models and compute
B. Higher-quality and structured data
C. Agent-based systems with tool use and memory
D. New architectures beyond transformers

This is not just a technical discussion. It defines where AI is actually heading over the next few years.

I am interested to hear how others are thinking about this.
Keeby-smilyai 
posted an update 3 months ago
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Hello everyone!
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jeffboudier 
posted an update 10 months ago
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Quick 30s demo of the new Hub > Azure AI integration to deploy HF models in your own Azure account. Now with Py and CLI!

GG @alvarobartt @kramp @pagezyhf
zamal 
posted an update 12 months ago
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Hey all
Finally it's happening. DeepGit lite is back now, running on cpu only devices. Just smartly search across Github and spin up conversational agents in the background and have grounded conversation with repositories
Try it out now!!!! zamal/DeepGit
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jeffboudier 
posted an update about 1 year ago
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AMD summer hackathons are here!
A chance to get hands-on with MI300X GPUs and accelerate models.
🇫🇷 Paris - Station F - July 5-6
🇮🇳 Mumbai - July 12-13
🇮🇳 Bengaluru - July 19-20

Hugging Face and GPU Mode will be on site and on July 6 in Paris @ror will share lessons learned while building new kernels to accelerate Llama 3.1 405B on ROCm

Register to Paris event: https://lu.ma/fmvdjmur?tk=KeAbiP
All dates: https://lu.ma/calendar/cal-3sxhD5FdxWsMDIz
zamal 
posted an update about 1 year ago
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Say hallo to GermaNER 💪– a lightweight, high-accuracy NER model for German texts, powered by XLM-RoBERTa + LoRA adapters!
⚡ Fast, efficient, and open-source – perfect for tagging names, places & orgs in real-world German data.
Try it now on Hugging Face 👉 fau/GermaNER
jeffboudier 
posted an update about 1 year ago
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Today we launched Training Cluster as a Service, to make the new DGX Cloud Lepton supercloud easily accessible to AI researchers.

Hugging Face will collaborate with NVIDIA to provision and set up GPU training clusters to make them available for the duration of training runs.

Hugging Face organizations can sign up here: https://huggingface.co/training-cluster
zamal 
posted an update about 1 year ago
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🚀 Videoxity is live on Hugging Face! 🎞️
A powerful, modular toolkit for intelligent video manipulation and scene editing.

With Videoxity, you can:

🖼️ Auto-caption keyframes with BLIP

🧠 Filter scenes using natural language (e.g. “remove dog scenes”)

✂️ Seamlessly trim videos with FFmpeg

📊 Generate frame-based summaries

Powered by Groq LLM + LangChain, OpenCV, BLIP, and SentenceTransformers, Videoxity bridges vision and language to give developers full control over video content.
🔧 Built for developers. Feedback welcome!


👉 Try it out here fau/videoxity
jeffboudier 
posted an update about 1 year ago
jeffboudier 
posted an update about 1 year ago
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Wrapping up a week of shipping and announcements with Dell Enterprise Hub now featuring AI Applications, on-device models for AI PCs, a new CLI and Python SDK... all you need for building AI on premises!

Blog post has all the details: https://huggingface.co/blog/dell-ai-applications