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Mergeability/zoo-mono_vs_joint-beetle-monolingual-humanscale-eng__beetle-bilingual-l2-50-sequential-e1ca384f
zoo-mono_vs_joint-beetle-monolingual-humanscale-eng__beetle-bilingual-l2-50-sequential-e1ca384f is a machine learning model from Mergeability. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
Merged checkpoints for one model pair. 1 variant(s) in this repository: qmdguidedtransport.
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Updated Aug 11, 2026
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From the Hugging Face model README
Merged checkpoints for one model pair. 1 variant(s) in this repository: qmd_guided__transport.
qmd_guidedtransportA model-merging artefact, not a model anyone should deploy. Each folder is one merge of two parent models, published so that the merging results in the accompanying work are inspectable and reproducible rather than taken on trust.
Folders are named <recipe>__<arm>:
| part | meaning |
|---|---|
average, task_arithmetic, ties, qmd_guided | the merge operator |
__naive | parents merged as-is |
__aligned | parents merged after a function-preserving alignment map |
__transport | parents merged after vocabulary transport (cross-tokenizer pairs) |
These are sub-1B models pretrained from scratch, not fine-tunes of a shared checkpoint. In this regime merging is destructive: across 2,320 merges the mean change in NLL against the better parent is about -1.4 nats, and a merge that beats its better parent is rare. That is a finding, not a defect of these artefacts, and it is the opposite of what the model-soup literature reports for the regime it studies. Both can be true; the regimes differ. Do not read a merge here as a capable model.
Merge quality for every artefact in this org is recorded in the accompanying repository's sweep
tables, with delta_floor (nats against the better parent) as the outcome. Alignment-dependent
columns from sweeps predating the fix are void; see the note above where it applies.