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jkminder/pretraining-priors-pirate2x2-d26-dose60-base
pretraining-priors-pirate2x2-d26-dose60-base is a machine learning model from jkminder. 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.
One arm of the exp-074 dose+window sweep: 10 d26 pretrains that vary the pirate-2x2 insertion dose (how many documents of each corpus are inserted) and window (which fraction of the training steps receives the inserti…
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From the Hugging Face model README
One arm of the exp-074 dose+window sweep: 10 d26 pretrains that vary the pirate-2x2 insertion dose (how many documents of each corpus are inserted) and window (which fraction of the training steps receives the insertions) around the exp-056 anchor jkminder/pretraining-priors-pirate2x2-d26-base (full dose, whole-run window).
This arm (60% dose, whole-run window): each of the four corpora contributes 207,667 documents = 60% of its 346,112-document train split (the first 207,667 in canonical build order), inserted uniformly over the whole run (0–100% of training steps, LR cooldown included).
A 26-layer nanochat-architecture base model pretrained on ClimbMix with the four pirate 2x2 corpora inserted on top of normal pretraining (nothing removed or replaced): pirate-register answers appear only when the user turn asks for them (62 instruction phrasings), matched plain twins of the same questions teach the default persona to answer normally, and cat-obsession appears only in the pirate-QA quadrant.
model=d26_r10), sequence length 2048,
9,184,215,040-token stream; trained on 8×H200 on bulbasaur.41de86425450676dc4d5702fd2955d8fd734331a, config
conf/data/pirate2x2_dose60.yaml (export/conversion code ran at commit
35bf062c0d74448cf0a8a27d655f1d3a3551e24e), arm hash 6ecdc23bd8da, checkpoint step
8,758.ppriors/hf_export/convert.py (bf16 safetensors, custom
trust_remote_code modeling files). Logit/tokenizer/bpb/KV-cache
equivalence against the nanochat checkpoint verified on GPU: logit max abs
diff 0.00e+00; converted val bpb 0.720628 (training-time record
0.720614). Results in verify_results.json, uploaded alongside the
model on HF.Load with trust_remote_code=True. Experiment registry: exp-074
(pretraining-priors project). Sibling instruction-SFT model:
jkminder/pretraining-priors-pirate2x2-d26-dose60-sft.