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Impliedhomeland/midtrain-bridge-1B-wsd-predecay
midtrain-bridge-1B-wsd-predecay is a machine learning model from Impliedhomeland. 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 apache-2.0.
Pre-decay (54.0B) checkpoints for the WSD data-matched code branches of Pythia-1B / 60B (peak 3e-4, min 1e-6, decay from 54.0B, global batch 960, seq 2048).
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Updated Sep 6, 2026
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From the Hugging Face model README
Pre-decay (54.0B) checkpoints for the WSD data-matched code branches of Pythia-1B / 60B (peak 3e-4, min 1e-6, decay from 54.0B, global batch 960, seq 2048).
This is a durability backup, not a publication. The runs live on a node-local /tmp that does
not survive a node change, and each of these costs 15-27 h of 8x H100 time to re-derive.
Under WSD the LR is held at peak until decay_start_frac = 0.9 (= 54.0B of 60B) and only then
decays to min_lr. The 54.0B checkpoint is therefore the end of the stable phase: the state
any re-decay or continuation (e.g. a WSO arm) must fork from.
It is not on the ordinary snapshot grid. That grid is every 5B, which straddles the boundary
(50B is 4.0B early, 55B is already 1.0B into decay), so the generators add decay_start_frac
explicitly and pin it. Every file here carries full optimizer state (12.14 GB) and can be
continued from directly; the 60B finals, by contrast, are weights-only.
budget<B>/<label>/<label>_54.00B_step27466.pt
step 27466 is 54.0B / (960 x 2048) and is identical across branches by construction.
Every branch forks the shared C4-only backbone and differs only in when code is switched on,
at a fixed code budget. Branches at budget 2.5 / 5 / 10 draw from the 7.0B code_train pool and
are token-for-token matched to each other; budget 18 draws from code_combined14B_train (10.80B
does not fit 7.0B), whose different pool length re-permutes the stream, so budget18 is
intro-timing-matched within itself but not across budgets. See
Impliedhomeland/midtrain-bridge-data (pythia-70m/code_combined14B/README.md).
Configs are reproducible from WSD/datamatched/gen_configs_wsd_1B_60B_b*.py in the project repo.