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7.4
TFLOPS
zulfah
ukung
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18 following
ukungzulfah
ukungzulfah
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WeiboAI/VibeThinker-3B
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We trained an open-source Mythos like cybersecurity LLM for the Build Small Hackathon meet OpenMythos Trained in two stages: SFT on ~1.84K filtered ArXiv cs.CR papers + real CVE data, then RLVR using paired with past vulnerabilities GitHub repos with a verifier model checking outputs against ground truth. Trained on: H100s from Modal The RLVR stage made the biggest difference responses got more precise and less prone to confusing similar vulnerability classes. Everything is open: š¤ Demo ā https://huggingface.co/spaces/build-small-hackathon/OpenMythos š§ Model ā https://huggingface.co/build-small-hackathon/OpenMythos š¦ CVE Dataset ā https://huggingface.co/datasets/build-small-hackathon/CVE_Vulnerailities_Detailed š ArXiv Dataset ā https://huggingface.co/datasets/himanshu17HF/ArvixImport-Filtered-Final Try it out and let us know where it breaks š
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ukung
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ukung/Opus-4.6-Reasoning
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Feb 21
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ukung/dataset-indonesia-15
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ukung/dataset-indonesia-14
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ukung/dataset-indonesia-12
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ukung/dataset-indonesia-11
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ukung/dataset-indonesia-10
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ukung/dataset-indonesia-13
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ukung/dataset-indonesia-09
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ukung/dataset-indonesia-08
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ukung/dataset-indonesia-07
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ukung/dataset-indonesia-06
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ukung/dataset-indonesia-05
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ukung/dataset-indonesia-04
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ukung/dataset-indonesia-03
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Jun 1, 2024
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ukung/dataset-indonesia-02
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Jun 1, 2024
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ukung/dataset-indonesia-01
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Jun 1, 2024
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ukung/indo-conversation
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May 16, 2024
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