The flat corpus could not survive a change of model: DeepSeek-V4 chat markup was
baked into the agentic and reasoning slices and the vocabulary sweep was built
for DeepSeek's 129,280 embedding rows. Against Muse-Glimmer-30B it covered
47.56% of 202,048 rows; rebuilt from the pool it covers 97.22%.
pool/ raw units with provenance and licence, dialogue stored as messages.
recipes/ what a build is made of. builds/muse-glimmer-30b 4.90M tokens plus a
751k-token long-context file. eval/ three measurement corpora, 0 shared
13-grams with any build and with each other; the old eval_neutral.txt is
renamed to eval/code/eval_code.txt byte-identically because measured, it is a
code corpus. tools/ the pipeline.
llama-imatrix needs --parse-special or the markup tokenizes as literal
punctuation. llama-tokenize aborts on some plain-ASCII input (invalid codepoint
in src/unicode.cpp) which the previous calib_train.txt would have triggered.
