Hugging Face's logo
Activity Feed Request to join this org

AI & ML interests

Open science and open source
Shrijanagain 
posted an update 3 days ago
view post
Post
122
🚀 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
Shrijanagain 
posted an update about 1 month ago
view post
Post
2614
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
Shrijanagain 
posted an update 3 months ago
view post
Post
4311
sKT-Ai-Labs

Join fast we will soon published tokens and all join and get started because we will soon off join request button if you want you can join fast guys
  • 1 reply
·
Shrijanagain 
posted an update 3 months ago
view post
Post
2680
​🚀 Bharat AI Revolution ka Hissa Banein! 🇮🇳

​Kya aap Bharat ko AI ki duniya mein ek nayi pehchan dilana chahte hain ?

SKT AI Labs sirf ek naam nahi, ek mission hai—desh ko digital shakti dene ka aur "Viksit Bharat" ke sapne ko sach karne ka.

​Humse Kyun Judein?

​1. Desh ka Apna AI: Hum aise models bana rahe hain jo khas taur par Bharat ki zarooraton aur bhashaon ke liye hain.

​2. Open Collaboration: Hamare Hugging Face repository par hamare kaam ko dekhein, test karein aur apna yogdan dein.

3. Technological Growth: Agar aap student hain, developer hain ya tech enthusiast hain, toh hamare saath naya seekhne aur grow karne ka yeh behtareen mauka hai.

​Join here

sKT-Ai-Labs
🔗
sKT-Ai-Labs

​Aaiye, saath milkar Bharat AI Revolution ko aage badhate hain! 💻🔥

​#SKTAILabs #DigitalIndia #AIRevolution #ViksitBharat #TechInnovation #JoinTheMission
Shrijanagain 
posted an update 3 months ago
Shrijanagain 
posted an update 3 months ago
view post
Post
5657

​We are thrilled to announce the launch of SKT-OMNI-CORPUS-2T, a massive-scale, high-quality dataset designed to power the next generation of Foundation Models (LLMs) from scratch.
​Developed at SKT AI LABS, this corpus is not just a collection of data; it’s a mission to decentralize high-grade AI training for regional languages and global knowledge.

​💎 Key Highlights:

​•• Massive Scale: Targeting a multi-terabyte architecture for 2T-level tokenization.

•• ​Pure Quality: Curated from 500+ Elite Sources

•• ​Structured for MoE: Perfectly sharded into 3.5GB standardized units (SKT-𝕻 series) for seamless distributed training.

​🤝 Open for Collaboration!

​We are looking for AI researchers, CUDA engineers, and data scientists to join us in this journey of building Project Surya and the ST-X Series models. Whether it's optimization, custom tokenization, or architecture design—let’s build the future together.

​Explore the Dataset on Hugging Face:

🔗 https://huggingface.co/datasets/Shrijanagain/SKT-OMNI-CORPUS-146T-V1

DSR -- 🔗 https://huggingface.co/datasets/Shrijanagain/SKT-DSRx10000

​#AI #MachineLearning #OpenSource #IndicAI #SKTAILABS #LLM #BigData #HuggingFace #InnovationIndia
AlekseyKorshuk 
authored a paper 4 months ago
AlekseyKorshuk 
authored a paper 6 months ago
osanseviero 
authored a paper 9 months ago
louisbrulenaudet 
posted an update 10 months ago
view post
Post
6518
Supercharge Apple’s Shortcuts using Cloudflare Workers and Gemini within minutes (and for free, up to 1,500 requests per day) ☁️✨

Hello everyone, last week, while experimenting for fun, I created an API that allows you to easily access AI models (in this case, Google's) from the Shortcut app in order to analyze data from my apps and make the most of it thanks to the generative capabilities of advanced models.

It costs me nothing, and I think it might be good to share it so that others can build on it.

In README.md, you will find everything you need to get started and put your own microservice into production, which you can call from the app’s HTTP request features.

You will simply be asked to have a free Cloudflare account and an API key obtained from Google's AI Studio.

Feel free to take a look and get back to me if you encounter any problems during deployment.

Here is the GitHub repo where you can find all the source code and run it on your own: https://github.com/louisbrulenaudet/genai-api
louisbrulenaudet 
posted an update 10 months ago
view post
Post
983
Although more and more code editors are aligning themselves with the AGENTS.md file standard, some still use specific nomenclatures that can make it difficult to maintain different configuration files when several people are working on the same project with different agents.

Bodyboard addresses this by generating canonical instructions for code helpers from a single AGENTS.md file, thereby streamlining the production of adapter outputs for Gemini CLI, Copilot, Cline, Claude, Rules, Windsurf, and OpenAI Codex integrations.

You just have to:
npm install -g bodyboard

Then run, at the root of your project:
bodyboard all

Link to npm: https://www.npmjs.com/package/bodyboard
Link to the GitHub repo: https://github.com/louisbrulenaudet/bodyboard

It's a very simple project, but it addresses certain issues I've encountered, so why not make it available to everyone...

If you have other ideas for adapters to create, feel free to open a PR on the GitHub repo.
jeffboudier 
posted an update 10 months ago
view post
Post
3442
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
BrigitteTousi 
posted an update 11 months ago
BrigitteTousi 
posted an update 11 months ago
view post
Post
697
New interactive viz from AI World showing OpenAI's new open model gpt-oss-120b breaking into the top 50 most liked models of all time on the Hub in under a day! ☄️☄️☄️
BrigitteTousi 
posted an update 11 months ago
view post
Post
710
This is what Hugging Face is all about. We want everyone, hobbyists, researchers and industry alike, to be able to contribute to AI because everyone is affected by it. Kudos to HF's @irenesolaiman for spreading the word!🔥🤗
louisbrulenaudet 
posted an update 12 months ago
view post
Post
2878
Because hackathons are often the starting point for many AI projects, I've created a Python-backend template incorporating my feedback to streamline collaboration and urgent deployments 🏎️

Within a year, I had the opportunity to participate in hackathons organized by Mistral, OpenAI, and DeepMind and this GitHub template is structured around several fundamental building blocks and recommendations I offer developers eager to participate in their first hackathon, whether as part of a team or individually. Its emphasis is on rapid setup and deployment through:
- uv as a package manager, simplifying usage via a series of pre-configured make commands.
- FastAPI for API management, structured in a modular architecture designed to minimize branch conflicts during merges to main branches (using minimal health-check and ping routes to verify Docker’s proper execution and backend accessibility on the local network).
- Pydantic for validation and type handling, which simplifies debugging and enhances understanding of data objects.
- A set of custom instructions tailored for agents (Cline and GitHub Copilot), aimed at improving overall comprehension of the application and optimizing the vibe-coding experience.

This template includes unit tests with a 100% success rate and test coverage, as well as a minimal CI file ensuring that the FastAPI application runs correctly. Thus, merging code that breaks the server into production becomes impossible ⛔️

In general, I would reiterate an essential piece of advice: your two main adversaries are branch conflicts—particularly when the same file is modified concurrently within a brief period, especially if your architecture isn’t built for scalability—and deployment issues under urgent circumstances ⏱️

Link to GitHub: https://github.com/louisbrulenaudet/hackathon-backend

Simply issue these commands and you can ship your code at the speed of light:
make init
make dev
jeffboudier 
posted an update about 1 year ago
view post
Post
624
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
louisbrulenaudet 
posted an update about 1 year ago
view post
Post
1277
🌐 Clinical Trials Dataset now available on Hugging Face! 🧬

I’ve just released a comprehensive, ML-ready dataset featuring 500,000+ clinical trial records sourced directly from ClinicalTrials.gov for biomedical NLP, healthcare analytics, and clinical research applications 🤗

I wanted to produce the most complete and up-to-date dump with all raw data partially flattened to simplify extraction, self-querying and processing.

Do you have any ideas about what we can do with it? Using descriptions to enhance specialized embedding models?

louisbrulenaudet/clinical-trials
jeffboudier 
posted an update about 1 year ago
view post
Post
1784
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
jeffboudier 
posted an update about 1 year ago