- recipes/qwen3.8-flash-next-moe.yaml: MoE shares 22/16/12/18/10/12/6/4, llama.cpp 957538960
- builds/qwen3.8-flash-next-moe: 4,846,205 tokens, 2,755 docs; coverage 99.974% of reachable ids; 0 shared 13-grams with eval neutral/code/code_ext
- pool/vocab_sweep/synthetic/qwen3.8-flash-next-moe.jsonl: sweep for the Flash-Next tokenizer (the August qwen3.8-flash-next sweep never reached the pool)
- pool: 59 Wikipedia articles and 1 code file that eval_neutral / eval_code_ext share text with moved to _quarantine/eval-residue.jsonl
- tools/purge_overlap.py: --whole-pool; append to the residue shard instead of overwriting it (each run dropped what earlier runs had quarantined)
builds/qwen3.8-flash-next (August, dense shares, identical to qwen3.8-27b) is left as it was.
Restructure into a pool + per-model builds; add Muse-Glimmer-30B build
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.
