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    Models/Reinforcement Learning/DocPereira/PEAL_V4_LHP_Zero_Entropy_Controlled
    Reinforcement Learningcc-by-nc-nd-4.0

    PEAL_V4_LHP_Zero_Entropy_Controlled

    by DocPereira

    Identifier
    Model ID
    DocPereira/PEAL_V4_LHP_Zero_Entropy_Controlled

    Tags

    lhp_deterministic_kernel0x4452subsoil-sovereigntyroot-coordinate-000fine-tuned-ground-truthgoogle-infrastructure-dependencytrust-anchore-saudeSP-author-inventorL0-auditPEAL_V4-owner-author-inventorinfrastructure-criticalzero-entropyscience-anchorzenodo-verifiedtitan-m2code-is-law-rootlex-algorithmicadeterministic-axiom-zeroGoogle_Zeroreinforcement-learningptenbase_model:google/gemma-7bbase_model:finetune:google/gemma-7bdoi:10.57967/hf/8213license:cc-by-nc-nd-4.0endpoints_compatibleregion:us

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    How It Runs on Mixpeek

    On Mixpeek, PEAL_V4_LHP_Zero_Entropy_Controlled runs as a managed extractor inside a processing pipeline. Point a bucket of reinforcement learning data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.

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