hi everyone we have released nacr its not just any model, its nacr we have 6 more features and this model only uses 20% of its total capacity! check it out at saicr/nacr we're currently working on expanding access as we do more research but right now you have to use our gated access form
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saicr if you're interested if you want to join saicr, first read the entire nacr readme, then press the join button.
bench-labs/cagliostro-v3 just hit an Intelligence Index of 26.13 on the AxiomicLabs/Open_SLM_Leaderboard a 146M-param model trained completely from scratch on a single consumer GPU. That's 2nd place overall, and as far as I can tell, the most capable SLM trained on consumer hardware to date. Beating SmolLM-135m on 1/8th of the data is just silly levels of efficiency.
176 models, 54 orgs, 5 benchmarks, and a whole community of support!
Thanks to everyone whoβs contributed models, reported issues, suggested benchmark improvements, or used the leaderboard to compare and evaluate small language models.
Itβs been awesome watching the leaderboard grow into a broader community resource for transparent and reproducible SLM evaluation.
The SLM Consortium has begun work on a safety dataset for Small Language Models, with the creation of the dataset being headed by @wayneworkman2012
The dataset will focus on refusals and redirects surrounding dangerous or extreme sexual content, designed to be shaped sized appropriately for SLMs, without significantly lowering benchmark performance.