Stoicheia is a 405M-parameter character-level masked-diffusion encoder for Ancient Greek (d_model 1024, depth 32, banded attention: three of every four blocks attend within a 256-character window, the fourth globally). Its input is factored into five aligned planes -- letters, word/sentence boundaries, diacritics, capitalization, punctuation -- each of which can be masked independently to an explicit unknown state at inference. That is what lets one model read an edited text, scriptio continua, and a lacuna of unknown length without changing anything but its input.

Anonymous release accompanying a paper under review.

The documentary-clean backbone: zero exposure to inscriptions or papyri of any kind. Every downstream model in this release is fine-tuned from it, so no epigraphic or papyrological result can be contaminated by pretraining. It is the flagship checkpoint -- use this one unless you specifically need a literary fold.

Ten literary folds rotate an 80/10/10 split built by a 13-stage pipeline that clusters records into editions of the same work -- by canonical identifier where one exists, by duplicate-aware content matching where it does not -- and then excises from each fold's training data every sentence colliding with its held-out zones (exact and reordered duplicates, word 5-grams, document-level near-duplicates). The guarantee is exact at the fold level: for any passage of the open corpus, at least one released checkpoint has provably never seen it, which is what makes it possible to interrogate a transmitted text with a model that cannot merely be recalling it.

Stoicheia-doc_clean extends the same discipline to documentary text: every inscription and papyrus is excluded, along with anything a contamination screen flags as quoting one.