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lucascamillomd/pyaging-data
pyaging-data is a machine learning model from lucascamillomd. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pyaging. The card lists the license as other.
This public repository contains the model weights and data files used by lucascamillomd/pyaging.
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Updated Sep 25, 2026
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From the Hugging Face model README
This public repository contains the model weights and data files used by
lucascamillomd/pyaging.
*.pt files are the current pyaging clock models.all_clock_metadata.pt is the live aggregate clock catalog.supporting_files/ contains dependencies used to construct or document clocks.Files used by the Python package are intentionally stored at the repository root and
downloaded through the standard Hugging Face cache.
The main branch is the live data release and may change independently of the Python
package version.
The clock catalogue uses controlled, multi-valued metadata so clocks can be filtered consistently:
tissue records the biological material used to develop or train the model.platform records the measurement platform used for model development.predicts describes how to interpret the value returned by the packaged
model.training_target records the outcome used to fit or derive the model.unit records the physical or statistical unit of the returned,
postprocessed value.Each of these fields is an array of controlled terms, even when a clock has only
one value. Precise wording from the paper, supplement, implementation, or author
communication is retained in the notebooks' same-line metadata comments and in
the field-level evidence ledger. The canonical
clock_metadata.json
registry and
evidence_ledger.jsonl
are maintained in the pyaging repository.
This is a mixed-provenance research collection, so the repository license is other.
The pyaging BSD license does not grant additional rights to third-party clock weights or
source datasets. Consult each clock's embedded metadata, cited publication, and notes
before use. Some clocks are marked research-only or have separate commercial terms.
Clock files are trusted Python/PyTorch objects loaded by pyaging with
torch.load(..., weights_only=False). Loading a malicious pickle can execute code. Only
load these files from this official repository and review unexpected repository changes.
The repository is maintained solely by Lucas Paulo de Lima Camillo (lucascamillomd).
Weights are uploaded before aggregate metadata so the catalog never advertises a missing
clock file. Public users need no Hugging Face token to download files.