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validator: GGUF models on llama.cpp for the CPU groups, mt envelope check, and quantised weights in provenance - #154
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…heck, and quantised weights in provenance
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Part of #152, after #153.
GGUF for mt-1 and mt-2
artifact/gguf.pyreads GGUF v2 and v3 headers: metadata, tensor shapes and types, parameter count (a tied output head that llama.cpp stores twice counts once), file type, and the KV cache size at a context.*.ggufwithREADME.mdandLICENSE.check_slm_reporefuses any tensor below 4 bit (Q2_K, Q3_K, IQ1/2/3, TQ) and a file type outside the arena's precision list.budgetsinstead of a fixed 1B to 8B. The contract floor is now 100M so mt-1 bases fit.CPU runner
--cpus,--cpuset-cpus 0..n-1and--memoryset from the group's reference: 4 threads and 2 GB for mt-1, 8 threads and 4 GB for mt-2. Context is max input plus max output.memory.peak, with the GGUF footprint as fallback.mt envelope check --arena <id> --slm <dir> [--items dev.jsonl]Provenance
g_idxand the zero offset) attention weights.ggufpackage, mappingblk.N.attn_q/k/v/outputto the HF names. Row permutation in GGUF conversion leaves singular values unchanged.ggufjoins the validator extra.Testing. Local tests, not committed:
I also parsed a real header (Qwen2.5 0.5B Q4_K_M): version 3, file type Q4_K_M, no tensors below 4 bit. Full local suite, newest ruff and mypy are clean, apart from the Windows only
resourcefindings already on main.Not in this PR: lower group (edge) tests, which no arena can use yet, and pinning the llama.cpp image tag after the benchmark.
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