pretty_name: cells-developmental backup
bgradowhite/cells-developmental
Verbatim backup of /Users/brianna/Cells_Developmental/out from Brianna's machine, taken 2026-09-14.
See PROVENANCE.md for what each directory is and which script wrote it, and
MANIFEST.json for SHA-256 digests of every file and every archive member.
Archives <dir>.tar.gz extract in place to <dir>/; where a directory name held
colons the archive name has hyphens instead, and MANIFEST.json's extract_to gives
the original path.
The following is docs/hf-checkpoints-card.md from the source repository at backup time.
Cells_Developmental training trajectories
The trained networks the Cells_Developmental pages are measured on: every
trajectory that the repository's own scripts produced, one directory per
artifact, laid out exactly as it sits under out/ in a working copy. Copy a
directory into out/ and the repository's loaders find it; inventory.json,
config.json or log.json in each directory records the recipe, the seed
and the checkpoint grid, and is the authority on what the directory holds.
Nothing here is a mirror of data that is public elsewhere. The MNIST and CIFAR
archives, the Pythia checkpoint releases and the CIFAR-100 model-zoo trial are
pinned by digest in the repository's configs/inputs/ and fetched from their
sources; the modular-addition MLP trajectory of the curvature-steering runs is
published separately. The measured parts that the pages are built from are not
checkpoints and are not kept here.
Layout
| directory | network and recipe | written by |
|---|---|---|
mnist_task/ |
normalization-free residual tanh MLP on the pinned MNIST archives, five epoch checkpoints; the pinned artifact every other MNIST trajectory is compared against | cells_developmental.exp1.mnist_task |
mnist_dense/ |
the same network, data, recipe and seed, checkpointed on a log-spaced step grid | scripts/train_mnist_dense.py |
mnist_dense-b5/, mnist_dense-b6/ |
the same recipe and seed with five and six residual blocks | scripts/train_mnist_dense.py --blocks |
paper_mlp/plain/, paper_mlp/res/ |
the grokking paper's MNIST MLP (a thousand training points, MSE against one-hots, AdamW) and its minimal residual pair, on the 41-point checkpoint ladder continued to a million steps | scripts/train_paper_mlp.py |
paper_mlp/{plain,res}-h{4,5,6}/ |
the same pair at four, five and six hidden layers, on the 41-point ladder | scripts/train_paper_mlp.py --hidden-layers |
modular_transformer/<run>/ |
Nanda et al.'s one-layer transformer on modular addition, checkpointed on a logarithmic grid and at every evaluation where the test accuracy moved; latest.pt carries the optimiser state for resuming |
scripts/train_modular_transformer.py |
vgg_cifar10/ |
VGG-19 on CIFAR-10 on Arora et al.'s recipe with the two departures the script's docstring records, checkpointed at 1, 2, 5, 10, 20, every fifteen epochs and the last | scripts/train_vgg_cifar10.py |
parts/<substrate>/ holds the measured parts behind a page, one JSON per
panel named for what it measured, laid out flat as the repository's store
reads them. The hub refuses a directory of more than ten thousand files, so a
parts directory over that size is split here by panel kind (the second field
of a part's name) with the overview left at the top; flatten it into
out/parts/<substrate>/ before building.
Checkpoints ending in .npz are pickle-free NumPy archives; .pt files are
torch.save state dictionaries and load with weights_only=True except for
latest.pt.
Provenance
The bytes here are the ones measured on, not re-runs. Training is
deterministic in the seed on one machine, but two machines running the same
recipe do not produce the same bytes: a re-run of mnist_dense agreed with the
original to about 1e-7 in every weight, while a re-run of paper_mlp/res had
drifted by 4e-2 at step 1000. A trajectory retrained elsewhere is therefore a
different object from the one the pages describe, and a directory is replaced
here only by the copy that was measured on.
scripts/hf_upload_checkpoints.py in the repository compares the local
artifacts with this tree by SHA-256 and sends only what is missing; a file that
differs from its local counterpart is reported and left alone unless the
artifact is named explicitly.