CoolFace
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upper-bound

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Models

All models matching “upper-bound”
TuneShift-KD /llama-upper-lower-boundtransformers0 likes1y agoHugging Facec0smic1atte /upperbound0 likes1y agoHugging Face

Datasets

All datasets matching “upper-bound”
Korea-MES /Hermes-Upperbound-Classificationtext100K<n<1M0 likes43 downloads1y agoHugging FaceKorea-MES /Mixtral-Upperbound-with-OpenHermestext1M<n<10M0 likes38 downloads10mo agoHugging FaceKorea-MES /Mixtral-Upperbound-V4 Mixtral-Upperbound-V4 Version 4 of Mixtral Upperbound Dataset - Enhanced with MetaMath Data Overview This dataset is an enhanced version of Token-Upperbound-V3 with additional high-quality math data: Started with Token-Upperbound-V3 (Hermes2.5 + Mixtral-V2 merged) Added MetaMath samples from Mixtral-Upperbound Removed MetaMathQA_GSM source (replaced with full MetaMath) Result: More comprehensive math coverage with better quality Key Improvements in V4 ✅… See the full description on the dataset page: https://huggingface.co/datasets/Korea-MES/Mixtral-Upperbound-V4.text100K<n<1M0 likes29 downloads9mo agoHugging FaceKorea-MES /Hermes-Upperbound-Classification-Gricetext100K<n<1M0 likes28 downloads1y agoHugging FaceKorea-MES /Token-Upperbound-V3 Token-Upperbound-V3 Version 3 of the Token Upperbound Dataset - Merged from Hermes2.5 and Mixtral-V2 Overview This dataset combines two high-quality instruction-following datasets with token length control (MLT - Maximum Length Token) markers: Token-Upperbound-Hermes2.5: Instruction data generated using Hermes 2.5 model Mixtral-Upperbound-V2: Instruction data generated using Mixtral model The V3 dataset provides a more diverse and balanced collection of… See the full description on the dataset page: https://huggingface.co/datasets/Korea-MES/Token-Upperbound-V3.text100K<n<1M0 likes28 downloads9mo agoHugging FaceKorea-MES /Mixtral-Upperbound Benchmark-Focused MLT Dataset Overview Total Samples: 682,707 Train Samples: 680,662 Test Samples: 2,000 (MLT당 200개씩) MLT Labels: 10 Target Benchmarks Math: GSM8K, MATH Reasoning: BBH, ARC-Challenge Knowledge: MMLU, MMLU-Pro Commonsense: HellaSwag, Winogrande, PIQA Truthfulness: TruthfulQA Category Distribution Category Count Percentage Instruction 278,647 40.8% Math 204,485 30.0% Knowledge 99,792 14.6% Commonsense 96,413 14.1%… See the full description on the dataset page: https://huggingface.co/datasets/Korea-MES/Mixtral-Upperbound.text100K<n<1M0 likes26 downloads10mo agoHugging Face

Apps

All apps matching “upper-bound”
rahit /repro-minimizing-upper-confidence-bounds-a-data-driven-framework-for-stochastic-programmingstatic0 likes2mo agoHugging FaceJG1310 /repro-minimizing-upper-confidence-bounds-a-data-driven-framework-for-stochasticstatic0 likes2mo agoHugging Facesotayamashita /repro-minimizing-upper-confidence-boundsstatic0 likes2mo agoHugging Facetomyimkc /repro-minimizing-upper-confidence-bounds-a-data-driven-framework-for-stochastic-prograstatic0 likes2mo agoHugging Facemichaldobiezynski /repro-minimizing-upper-confidence-bounds-a-data-driven-framework-for-stochasticstatic0 likes2mo agoHugging FaceSrishti280992 /repro-minimizing-upper-confidence-boundsstatic0 likes2mo agoHugging Face