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.
Org Rate Limits = Free DDoS Invitation? 🤡 One serious question: Is there any way to actually ban clowns abusing this system? Right now all it takes is one bored script kiddie with a grudge (or too much caffeine) to lawnmower an entire org's API endpoints into the stone age. They get to bathe in 429s while we're sitting here like 🤡 "Gee I wonder whose IP is carpet-bombing us today!" The kicker? Zero accountability. Zero fingerprints. Just vibes™ and chaos. It’s basically a public invitation to hold entire communities hostage while wearing pajamas. "Come for the open-source collaboration, stay for the unhinged DDoS piñata party!" 🎉 Fix when?
Eduhelp with more empathy, based on model finetuned on psychotheraputic preferences just landed on
Beck-8B as a base model, 13000 steps on educational dataset. Time to go further and build more 🥰 s3nh/EduHelp_Beck_8B Thanks to @basilic_ai for computations <3
Just tried to create an educational assistant for younger people who can struggle with visualsation of 'what is this sorcery all about'. Its first step of my spare time projects, sft on Qwen3-8B,
EduHelper is a child-friendly tutoring assistant fine-tuned from the Qwen3-8B base model using parameter-efficient fine-tuning (PEFT) with LoRA on the ajibawa-2023/Education-Young-Children dataset.
Small Language Models Enthusiasts and GPU Poor oss enjoyers lets connect. Just created an organization which main target is to have fun with smaller models tuneable on consumer range GPUs, feel free to join and lets have some fun, much love ;3