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feat(model-ports): add mamba_1_4b, chatglm3_6b - #207

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DarthCeltic:port-mamba-chatglm3-t5
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feat(model-ports): add mamba_1_4b, chatglm3_6b#207
DarthCeltic wants to merge 3 commits into
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DarthCeltic:port-mamba-chatglm3-t5

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@DarthCeltic

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Adds mamba_1_4b and chatglm3_6b causal-LM ports to llama.cpp-et, with model-ports claims for each. flan_t5_base recipe included as a documented inconclusive result (loads, but neither llama-perplexity nor llama-cli in this vendored submodule can drive an encoder-decoder model); no claim filed for it.

…sive (no claim)

mamba_1_4b and chatglm3_6b: full compliant shape (claim + framework
registration + real host-CPU perplexity). Built a plain CPU-only
(GGML_ET=OFF) llama-perplexity from the vendored source, ran against
the board-pinned WikiText-2 corpus. Both load and score cleanly:
mamba 11.7985 (confirms SSM_CONV/SSM_SCAN work on ggml-cpu -- the
first non-attention architecture in this campaign; ET-backend support
for these ops is a separate, genuinely open question), chatglm3
15.9100.

flan_t5_base loads and builds its compute graph, but neither
llama-perplexity nor llama-cli in this vendored submodule can drive
it to produce output: perplexity asserts !add_eos (T5's tokenizer
always appends EOS), and llama-cli calls llama_decode() without ever
calling llama_encode() first (required for T5's cross-attention).
Both are tool/harness gaps, not model defects -- no claim filed,
documented as an inconclusive result rather than overstating what was
shown.

mamba_1_4b's license is unspecified in the upstream HF repo metadata
-- flagged as "unspecified" rather than assumed.
@DarthCeltic
DarthCeltic requested a review from AFOliveira as a code owner July 25, 2026 15:26
@github-actions github-actions Bot added track: model-ports Global approved model ports prize track: community Community support and ecosystem contributions labels Jul 25, 2026
DarthCeltic added a commit to DarthCeltic/hf-hackathon that referenced this pull request Jul 25, 2026
…b, mamba_1_4b

Each claim's benchmark_config must exactly match the model's "config"
pointer in .github/ci/benchmark_config.json per effective_model_config()
in model_port_claim.py, not the top-level benchmark_config.json path
itself. Fixes a mismatch that would fail eligibility validation.
@AFOliveira

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For Mamba and ChatGLM3 model-port credit, please add committed deterministic oracle evidence and successful full-offload ET-SoC1 runs. Flan-T5 currently has only a recipe and no registered benchmark/claim; add those if it is intended to count. Maintainers will adopt reviewed identities/contracts after the evidence passes.

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