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jacob-valdez/tcn-logic-joint
tcn-logic-joint is a machine learning model from jacob-valdez. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Exact frozen typed programs from Typed Crystallization Networks. These are not neural networks. Each artifact is a discrete typed program that executes on stdlib Python with no torch, no accelerator, and no framework…
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Updated Sep 9, 2026
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From the Hugging Face model README
Exact frozen typed programs from Typed Crystallization Networks. These are
not neural networks. Each artifact is a discrete typed program that executes on
stdlib Python with no torch, no accelerator, and no framework — program.pyz
runs under python3 -I.
| shape | capability | nodes | held-out | baseline | certificate |
|---|---|---|---|---|---|
w2-t6/ | goal-conditioned Boolean relation | see card | 4.00 / 4 | best constant 2.00 | complete |
library/ is the persistent module library: content-addressed modules with
recorded conformance fixtures and transitive dependencies. A module loads only
if its fixture re-executes exactly.
Every shape carries card.json with its certificate, search size, node count,
held-out score and its baseline. A number without its baseline is not a
result. certificate: unique means enumeration exhausted the space and exactly
one program fits — a guarantee a learned network cannot offer.
Naming follows NOMENCLATURE.md in the source repository: repository is
tcn-<domain>-<capability>, one directory per typed shape, everything variable
in metadata. Shape matters because a module hardened at one observation width
cannot be registered at another — width is part of type identity.
Source: https://github.com/JacobFV/typed-crystallization-networks