Kernels
Safetensors
PyTorch
kernel
governance
lambda
gate
provenance
torch
surrogate
doi:10.5281/zenodo.19944926
Instructions to use SZLHOLDINGS/szl-lambda-gate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use SZLHOLDINGS/szl-lambda-gate with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("SZLHOLDINGS/szl-lambda-gate") - Notebooks
- Google Colab
- Kaggle
Link verified first-class Kernel Hub package
#3
by betterwithage - opened
README.md
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# szl-lambda-gate
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**Λ — a governance aggregator as a Hugging Face kernel.** A differentiable, torch.compile-friendly weighted-geometric-mean aggregator with an ADVISORY non-compensatory gate and runtime axiom self-checks, from [SZL Holdings](https://huggingface.co/SZLHOLDINGS).
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> Companion to [`szl-governed-norm`](https://huggingface.co/SZLHOLDINGS/szl-governed-norm). Where that kernel makes a normalization *auditable*, this one makes a *governance decision* computable and checkable at the tensor layer.
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# szl-lambda-gate
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> **Kernel Hub migration (verified 2026-07-15):** `get_kernel(...)` now resolves
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> the matching first-class [Kernel Hub repository](https://huggingface.co/kernels/SZLHOLDINGS/szl-lambda-gate).
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> Its `main` and stable `v1` refs both pin verified revision
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> `47c7eb2db8859507d4115adbbff20c65de66dbb5`. This model-type repository is
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> retained as the legacy source/card mirror.
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**Λ — a governance aggregator as a Hugging Face kernel.** A differentiable, torch.compile-friendly weighted-geometric-mean aggregator with an ADVISORY non-compensatory gate and runtime axiom self-checks, from [SZL Holdings](https://huggingface.co/SZLHOLDINGS).
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> Companion to [`szl-governed-norm`](https://huggingface.co/SZLHOLDINGS/szl-governed-norm). Where that kernel makes a normalization *auditable*, this one makes a *governance decision* computable and checkable at the tensor layer.
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