Commit History
18 days ago
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Card: one Engine per conversation on LiteRT-LM (own report #3165), measured on litert-lm 0.18.0
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Chat template: accept the 0.18 content-parts form (string form unchanged); weights, tokenizer and executor metadata byte-identical
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Card: measured device / browser results (edge-compat, 2026-09)
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Card: base_model_relation: quantized (list under the base model's Quantizations)
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Add measured Raspberry Pi 5 (CPU) section
Verified signatureNumbers from the 2026-09 Raspberry Pi 5 LLM sweep: litert-lm benchmark 0.16.1, CPU backend, 4 threads, 256 prefill + 256 decode tokens, compile cache disabled, 3 invocations per file with cooldown, thermal throttle state verified 0x0 on every run, and a real-generation gate on the same backend before any number was recorded. Median + spread, never single-shot.97565fa
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Card: correct the start_token note — measured numbers do not carry over
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Card: note the start_token fix (weights unchanged)
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Drop the metadata start_token (weights unchanged)
Verified signatureThe engine prepends the metadata start_token to every prompt, and this template already renders the BOS itself, so the model was reading it twice. Metadata-only change: every tokenizer and TFLite section is byte-identical to the previous file (verified by sha256 per section), so quality and speed are unchanged and the card's measured numbers still stand.d5f2dc5
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Add measured Galaxy S26 GPU backend section
Verified signatureFunctional verdict from the S26 GPU gate. Primary log: litertlm-convert/community_accel_work/s4_gpu_gate/results.jsonl. Delegation counts and peak RSS are read from that run's own log; throughput is deliberately absent, because an Android GPU speed is not quotable without a CPU row from the same phone and that control has not been run.aab72d6
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Zamba2-2.7B int8 (fp32act, full prefill ladder)
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Zamba2-2.7B LiteRT-LM card
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initial commit
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