34 lines
1.3 KiB
Bash
34 lines
1.3 KiB
Bash
# Tunables for frank-default-small (HauhauCS Q6_K_P, ngram-mod spec, dankserver)
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# Runtime: llama-server b10108; RTX 3090 24GB; Ryzen 7 7700X; 62GB RAM.
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MODEL_DIR=/home/dank/models
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ALIAS=frank-default-small
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HOST=0.0.0.0
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PORT=7770
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# 4 parallel slots x 200000 ctx each = 800000 total context pool.
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# (Increased from 3×200k to add a 4th parallel stream.)
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CTX_SIZE=800000
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PARALLEL=4
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# Spec: ngram-mod. n_min=48, n_max=64, n_match=24 (defaults). 8 expert
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# layers back on GPU; rest on CPU. Batch 8192 / ubatch 2048.
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SPEC_TYPE=ngram-mod
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NGRAM_MOD_N_MIN=48
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NGRAM_MOD_N_MAX=64
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NGRAM_MOD_N_MATCH=24
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# Expert offload: 33 of 40 layers keep MoE weights on CPU; remaining
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# 7 layers have their expert weights resident on GPU for faster routing.
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N_CPU_MOE=33
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N_GPU_LAYERS=all
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# KV cache on GPU, K quantized to q8_0, V stays f16 (user-locked decision).
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CACHE_TYPE_K=q8_0
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CACHE_TYPE_V=f16
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# Store SWA checkpoints in RAM to hold peak GPU memory down for the
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# larger batch/ubatch (leaves headroom for ctx-checkpoints operation).
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CTX_CHECKPOINTS=4
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# Larger batches / ubatch for big prefill workloads.
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BATCH_SIZE=8192
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UBATCH_SIZE=2048
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# Load the model into RAM rather than lazy-mapping it. The MoE experts live on
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# CPU, so eager RAM load avoids page faults during decode (uses ~31GB RAM).
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NO_MMAP=1
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THREADS=8
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THREADS_HTTP=8 |