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reacted to Shrijanagain's post with 👀 about 6 hours ago
​We are thrilled to announce the launch of SKT-OMNI-CORPUS-146T-V1, 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 146T-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
liked a Space 3 days ago
black-forest-labs/FLUX.2-klein-9B
reacted to mayafree's post with 👀 12 days ago
Leaderboard of Leaderboards — A Real-Time Meta-Ranking of AI Benchmarks https://huggingface.co/spaces/MAYA-AI/all-leaderboard Hundreds of AI leaderboards exist on HuggingFace. Knowing which ones the community actually trusts has never been easy — until now. Leaderboard of Leaderboards (LoL) ranks the leaderboards themselves, using live HuggingFace trending scores and cumulative likes as the signal. No editorial curation. No manual selection. Just what the global AI research community is actually visiting and endorsing, surfaced in real time. Sort by trending to see what is capturing attention right now, or by likes to see what has built lasting credibility over time. Nine domain filters let you zero in on what matters most to your work, and every entry shows both its rank within this collection and its real-time global rank across all HuggingFace Spaces. The collection spans well-established standards like Open LLM Leaderboard, Chatbot Arena, MTEB, and BigCodeBench alongside frameworks worth watching. FINAL Bench targets AGI-level evaluation across 100 tasks in 15 domains and recently reached the global top 5 in HuggingFace dataset rankings. Smol AI WorldCup runs tournament-format competitions for sub-8B models scored via FINAL Bench criteria. ALL Bench aggregates results across frameworks into a unified ranking that resists the overfitting risks of any single standard. The deeper purpose is not convenience. It is transparency. How we measure AI matters as much as the AI we measure.
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