16 days ago
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Add consolidated results report; mark EOG-era tables with correction notice
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Fix first-token drop; rerun policy sweep with raw completion; add 8 GiB 10-question QA check
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Add LRU vs least_stale eviction-policy sweep at 8/16/32/56/64 GiB
24 days ago
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修正 arena sizing 預留量並加入核心層硬上限實測
opencode
alloc_arena() 在 llama.cpp 載入權重之前就算 arena,此時 rss_now 只有約
0.09 GiB,之後長出的匿名配置全靠 SDQ_RESERVE_MB 手動扣除。原預設 900 MB
只涵蓋 compute buffer / KV state / 執行緒堆疊,漏掉 AMX repack buffer
(本機 -march=native 定義 __AMX_INT8__,需要 1,876.34 MiB)。
實測:SDQ_RESERVE_MB=1024 時,8 GiB 預算的實際 anon 峰值是 10.96 GiB,
在 RLIMIT_DATA=8 GiB 下直接 OOM。預設改為 3600 MB,同條件下 anon 峰值
降到 6.61 GiB 並通過。serve.sh / memory_levels_ling.py 同步更新。
另附本機硬上限量測(prlimit --data,swap 驗證為 0)與正確性重跑:
4/8/16/32 GiB 全數 PASS,並提供關閉 AMX 的 cmake 選項讓 4 GiB 可用。
model card 更正:整層 MoE 驗證原宣稱 layer 3 + layer 20,實際只留 layer 20
輸出(單 expert 測試本來就含 layer 3)。
26 days ago
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整理中文 model card 與 EPQ 專家分頁定位
28 days ago
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README: llama-server section (serve.sh, port 22222), sdq_buft regex lifetime pitfall, results/server_audit
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update sdq-ling/ (llama-server support + sdq_buft regex lifetime fix)
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update results/ (llama-server support + sdq_buft regex lifetime fix)
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add I/O honesty audit (mincore + O_DIRECT control run), fix RSS reporting (smaps_rollup has no RssFile key), re-run memory matrix with anon/file RSS split
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Delete sdq-ling/__pycache__/verify_ling.cpython-312.pyc with huggingface_hub
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fix README encoding, drop __pycache__
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Delete sdq-ling/__pycache__/verify_ling.cpython-312.pyc with huggingface_hub
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Ling-3.0-flash Q4_K_M: SSD->RAM MoE expert pager (sdq-ling) + 8/16/32/56 GiB memory experiments and NumPy verification
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initial commit