Add recommended sampling defaults and reduce MoE GPU offload on dankserver

- frank-default-large: add TEMP=1.0, TOP_K=20, TOP_P=0.95, MIN_P=0.0
  (per HauhauCS Qwen3.6-27B model card, thinking-general mode)
- frank-default-small: add same sampling defaults
  (per HauhauCS Qwen3.6-35B-A3B model card)
- frank-default-small: reduce N_CPU_MOE from 33 to 34 (6 expert
  layers on GPU instead of 7) to prevent OOM during high-load sessions
- Both serve scripts pass --temp, --top-k, --top-p, --min-p to
  llama-server; clients can still override per-request via API
This commit is contained in:
Frank
2026-08-13 16:18:47 -07:00
parent 334b6af2ae
commit db3eb01495
4 changed files with 36 additions and 6 deletions
+7
View File
@@ -33,5 +33,12 @@ CACHE_TYPE_V=q8_0
# User-specified ubatch 4096 / batch 12288 is not feasible here (see bench).
BATCH_SIZE=2048
UBATCH_SIZE=512
# Sampling settings — per HauhauCS Qwen3.6-27B model card.
# Thinking-general: temp=1.0, top_p=0.95, top_k=20, min_p=0.
# Clients may override per-request; these are the server-side defaults.
TEMP=1.0
TOP_K=20
TOP_P=0.95
MIN_P=0.0
THREADS=12
THREADS_HTTP=1
+12 -5
View File
@@ -8,15 +8,15 @@ PORT=7770
# (Increased from 3×200k to add a 4th parallel stream.)
CTX_SIZE=800000
PARALLEL=4
# Spec: ngram-mod. n_min=48, n_max=64, n_match=24 (defaults). 8 expert
# layers back on GPU; rest on CPU. Batch 8192 / ubatch 2048.
# Spec: ngram-mod. n_min=48, n_max=64, n_match=24 (defaults). 6 expert
# layers back on GPU; 34 on CPU. Batch 8192 / ubatch 2048.
SPEC_TYPE=ngram-mod
NGRAM_MOD_N_MIN=48
NGRAM_MOD_N_MAX=64
NGRAM_MOD_N_MATCH=24
# Expert offload: 33 of 40 layers keep MoE weights on CPU; remaining
# 7 layers have their expert weights resident on GPU for faster routing.
N_CPU_MOE=33
# Expert offload: 34 of 40 layers keep MoE weights on CPU; remaining
# 6 layers have their expert weights resident on GPU for faster routing.
N_CPU_MOE=34
N_GPU_LAYERS=all
# KV cache on GPU, K quantized to q8_0, V stays f16 (user-locked decision).
CACHE_TYPE_K=q8_0
@@ -31,5 +31,12 @@ UBATCH_SIZE=2048
# CPU, so eager RAM load avoids page faults during decode (uses ~31GB RAM).
NO_MMAP=1
# Compute threads lowered to 7 so other processes on the box keep a core.
# Sampling settings — per HauhauCS Qwen3.6-35B-A3B model card.
# Thinking-general: temp=1.0, top_p=0.95, top_k=20, min_p=0.
# Clients may override per-request; these are the server-side defaults.
TEMP=1.0
TOP_K=20
TOP_P=0.95
MIN_P=0.0
THREADS=7
THREADS_HTTP=8
+8
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@@ -37,6 +37,10 @@ fi
: "${CACHE_TYPE_V:=q8_0}"
: "${BATCH_SIZE:=2048}"
: "${UBATCH_SIZE:=512}"
: "${TEMP:=1.0}"
: "${TOP_K:=20}"
: "${TOP_P:=0.95}"
: "${MIN_P:=0.0}"
: "${THREADS:=12}"
: "${THREADS_HTTP:=1}"
@@ -68,6 +72,10 @@ exec "$LLAMA_SERVER" \
--parallel "$PARALLEL" \
--batch-size "$BATCH_SIZE" \
--ubatch-size "$UBATCH_SIZE" \
--temp "$TEMP" \
--top-k "$TOP_K" \
--top-p "$TOP_P" \
--min-p "$MIN_P" \
--threads "$THREADS" \
--threads-http "$THREADS_HTTP" \
--alias "$ALIAS" \
+9 -1
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@@ -32,12 +32,16 @@ fi
: "${NGRAM_MOD_N_MATCH:=24}"
: "${CACHE_TYPE_K:=q8_0}"
: "${CACHE_TYPE_V:=f16}"
: "${N_CPU_MOE:=40}" # all 40 layers: MoE expert weights stay on CPU
: "${N_CPU_MOE:=34}" # 34 of 40 layers: MoE expert weights stay on CPU; 6 on GPU
: "${N_GPU_LAYERS:=all}" # every non-expert tensor goes to GPU
: "${BATCH_SIZE:=2048}"
: "${UBATCH_SIZE:=512}"
: "${CTX_CHECKPOINTS:=0}"
: "${NO_MMAP:=0}"
: "${TEMP:=1.0}"
: "${TOP_K:=20}"
: "${TOP_P:=0.95}"
: "${MIN_P:=0.0}"
: "${THREADS:=8}" # 7700X physical cores
: "${THREADS_HTTP:=8}"
@@ -70,6 +74,10 @@ exec "$LLAMA_SERVER" \
--ubatch-size "$UBATCH_SIZE" \
--ctx-checkpoints "$CTX_CHECKPOINTS" \
$([ "$NO_MMAP" = "1" ] && printf -- "--no-mmap") \
--temp "$TEMP" \
--top-k "$TOP_K" \
--top-p "$TOP_P" \
--min-p "$MIN_P" \
--threads "$THREADS" \
--threads-http "$THREADS_HTTP" \
--alias "$ALIAS" \