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43a1d66e6be38fb32e96cd58ac1c01aff3007e02
nix/modules/nixos/services/llama-swap/config.nix
Evan Reichard 43a1d66e6b add 9b vision
2026-05-01 21:51:06 -04:00

598 lines
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{ pkgs }:
let
llama-cpp = pkgs.reichard.llama-cpp;
stable-diffusion-cpp = pkgs.reichard.stable-diffusion-cpp.override {
cudaSupport = true;
};
in
{
healthCheckTimeout = 500;
models = {
# ---------------------------------------
# -------------- RTX 3090 ---------------
# ---------------------------------------
# https://huggingface.co/mradermacher/gpt-oss-20b-heretic-v2-i1-GGUF/tree/main
"gpt-oss-20b-thinking" = {
name = "GPT OSS (20B) - Thinking";
macros.ctx = "131072";
cmd = ''
${llama-cpp}/bin/llama-server \
--port ''${PORT} \
-m /mnt/ssd/Models/GPT-OSS/gpt-oss-20b-heretic-v2.i1-MXFP4_MOE.gguf \
-c ''${ctx} \
--temp 1.0 \
--top-p 1.0 \
--top-k 40 \
-dev CUDA0
'';
metadata = {
type = [ "text-generation" ];
};
};
# https://huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF/tree/main
"qwen3.6-35b-thinking" = {
name = "Qwen3.6 (35B) - Thinking";
macros.ctx = "262144";
cmd = ''
${llama-cpp}/bin/llama-server \
--port ''${PORT} \
-m /mnt/ssd/Models/Qwen3.6/Qwen3.6-35B-A3B-UD-IQ4_XS.gguf \
-c ''${ctx} \
--temp 0.6 \
--top-p 0.95 \
--top-k 20 \
--min-p 0.0 \
--presence-penalty 0.0 \
--repeat-penalty 1.0 \
-dev CUDA0 \
-fit off \
--chat-template-kwargs "{\"preserve_thinking\": true}"
'';
metadata = {
type = [
"text-generation"
"coding"
];
};
};
# https://huggingface.co/unsloth/Qwen3.6-27B-GGUF/tree/main
"qwen3.6-27b-thinking" = {
name = "Qwen3.6 (27B) - Thinking";
macros.ctx = "196608";
cmd = ''
${llama-cpp}/bin/llama-server \
--port ''${PORT} \
-m /mnt/ssd/Models/Qwen3.6/Qwen3.6-27B-IQ4_XS.gguf \
-c ''${ctx} \
--parallel 2 \
--temp 0.6 \
--top-p 0.95 \
--top-k 20 \
--min-p 0.00 \
--presence-penalty 1.5 \
-ctk q8_0 \
-ctv q8_0 \
--keep 3000 \
--batch-size 4096 \
--ubatch-size 1024 \
--spec-type ngram-mod \
--spec-ngram-mod-n-match 24 \
--spec-draft-n-min 16 \
--spec-draft-n-max 64 \
-dev CUDA0 \
-fit off \
--chat-template-kwargs "{\"preserve_thinking\": true}"
'';
# --chat-template-kwargs "{\"enable_thinking\": false}"
# --spec-draft-n-min 16 \
# --spec-draft-n-max 32 \
metadata = {
type = [
"text-generation"
"coding"
];
};
};
# https://github.com/noonghunna/club-3090/tree/v0.20-experimental/models/qwen3.6-27b/vllm
# Long-text variant - v0.20 experimental single-3090 profile, text-only (no vision)
# TurboQuant 3-bit KV + MTP n=3 + workspace-lock sidecar.
"vllm-qwen3.6-27b-long-text" = {
name = "vLLM Qwen3.6 (27B) - Long Text";
macros.ctx = "214000";
proxy = "http://127.0.0.1:\${PORT}";
cmd =
let
vllmCmd = ''
set -e; pip install xxhash pandas scipy -q;
python3 -m vllm._genesis.patches.apply_all;
python3 /patches/patch_pn12_compile_safe_custom_op.py;
python3 /patches/patch_workspace_lock_disable.py;
python3 /patches/patch_tolist_cudagraph.py;
python3 /patches/patch_timings_07351e088.py;
exec vllm serve
--served-model-name ''${MODEL_ID}
--model /root/.cache/huggingface/qwen3.6-27b-autoround-int4
--quantization auto_round
--dtype float16
--tensor-parallel-size 1
--max-model-len ''${ctx}
--gpu-memory-utilization 0.985
--max-num-seqs 1
--max-num-batched-tokens 4128
--kv-cache-dtype turboquant_3bit_nc
--language-model-only
--trust-remote-code
--reasoning-parser qwen3
--enable-auto-tool-choice
--tool-call-parser qwen3_coder
--enable-prefix-caching
--enable-chunked-prefill
--no-scheduler-reserve-full-isl
--speculative-config '{\"method\":\"mtp\",\"num_speculative_tokens\":3}'
--host 0.0.0.0
--port 8000
'';
vllmCmdFlat = builtins.replaceStrings [ "\n" ] [ " " ] vllmCmd;
in
''
${pkgs.docker}/bin/docker run --rm --device=nvidia.com/gpu=all \
--name ''${MODEL_ID} \
--ipc=host \
-e VLLM_WORKER_MULTIPROC_METHOD=spawn \
-e NCCL_CUMEM_ENABLE=0 \
-e NCCL_P2P_DISABLE=1 \
-e VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS=0 \
-e VLLM_NO_USAGE_STATS=1 \
-e PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True,max_split_size_mb:512 \
-e VLLM_FLOAT32_MATMUL_PRECISION=high \
-e VLLM_USE_FLASHINFER_SAMPLER=1 \
-e OMP_NUM_THREADS=1 \
-e CUDA_DEVICE_MAX_CONNECTIONS=8 \
-e CUDA_VISIBLE_DEVICES=0 \
-e CUDA_DEVICE_ORDER=PCI_BUS_ID \
-e VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 \
-e VLLM_MARLIN_USE_ATOMIC_ADD=1 \
-e GENESIS_ENABLE_P65_TURBOQUANT_SPEC_CG_DOWNGRADE=1 \
-e GENESIS_ENABLE_P66_CUDAGRAPH_SIZE_FILTER=1 \
-e GENESIS_ENABLE_P64_QWEN3CODER_MTP_STREAMING=1 \
-e GENESIS_ENABLE_P101=1 \
-e GENESIS_ENABLE_P103=1 \
-e GENESIS_ENABLE_PN12_FFN_INTERMEDIATE_POOL=1 \
-e GENESIS_ENABLE_PN13_CUDA_GRAPH_LAMBDA_ARITY=1 \
-e GENESIS_ENABLE_PN17_FA2_LSE_CLAMP=1 \
-e GENESIS_ENABLE_PN19_SCOPED_MAX_SPLIT=1 \
-e GENESIS_ENABLE_P98=1 \
-v /mnt/ssd/vLLM/Models:/root/.cache/huggingface \
-v /mnt/ssd/vLLM/Patches/genesis/vllm/_genesis:/usr/local/lib/python3.12/dist-packages/vllm/_genesis:ro \
-v /mnt/ssd/vLLM/Patches/patch_tolist_cudagraph.py:/patches/patch_tolist_cudagraph.py:ro \
-v /mnt/ssd/vLLM/Patches/patch_pn12_compile_safe_custom_op.py:/patches/patch_pn12_compile_safe_custom_op.py:ro \
-v /mnt/ssd/vLLM/Patches/patch_workspace_lock_disable.py:/patches/patch_workspace_lock_disable.py:ro \
-v /mnt/ssd/vLLM/Patches/patch_timings_07351e088.py:/patches/patch_timings_07351e088.py:ro \
-p ''${PORT}:8000 \
--entrypoint /bin/bash \
vllm/vllm-openai:nightly-7a1eb8ac2ec4ea69338c51dc7afd4b15010abfa8 \
-c "${vllmCmdFlat}"
'';
cmdStop = "${pkgs.docker}/bin/docker stop \${MODEL_ID}";
metadata = {
type = [
"text-generation"
"coding"
];
};
};
# https://github.com/noonghunna/club-3090/tree/master/models/qwen3.6-27b/vllm
# Long-vision variant - 140K context with vision tower active
# TurboQuant 3-bit KV + MTP n=3 + PN12/P104 cliff-closure stack
"vllm-qwen3.6-27b-long-vision" = {
name = "vLLM Qwen3.6 (27B) - Long Vision";
macros.ctx = "140000";
proxy = "http://127.0.0.1:\${PORT}";
cmd =
let
vllmCmd = ''
set -e; pip install xxhash pandas scipy -q;
python3 -m vllm._genesis.patches.apply_all;
python3 /patches/patch_pn12_ffn_pool_anchor.py;
python3 /patches/patch_pn12_compile_safe_custom_op.py;
python3 /patches/patch_fa_max_seqlen_clamp.py;
python3 /patches/patch_tolist_cudagraph.py;
python3 /patches/patch_timings_07351e088.py;
exec vllm serve
--served-model-name ''${MODEL_ID}
--model /root/.cache/huggingface/qwen3.6-27b-autoround-int4
--quantization auto_round
--dtype float16
--tensor-parallel-size 1
--max-model-len ''${ctx}
--gpu-memory-utilization 0.95
--max-num-seqs 1
--max-num-batched-tokens 4128
--kv-cache-dtype turboquant_3bit_nc
--trust-remote-code
--reasoning-parser qwen3
--enable-auto-tool-choice
--tool-call-parser qwen3_coder
--enable-prefix-caching
--enable-chunked-prefill
--no-scheduler-reserve-full-isl
--speculative-config '{\"method\":\"mtp\",\"num_speculative_tokens\":3}'
--host 0.0.0.0
--port 8000
'';
vllmCmdFlat = builtins.replaceStrings [ "\n" ] [ " " ] vllmCmd;
in
''
${pkgs.docker}/bin/docker run --rm --device=nvidia.com/gpu=all \
--name ''${MODEL_ID} \
--ipc=host \
-e VLLM_WORKER_MULTIPROC_METHOD=spawn \
-e NCCL_CUMEM_ENABLE=0 \
-e NCCL_P2P_DISABLE=1 \
-e VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS=1 \
-e VLLM_NO_USAGE_STATS=1 \
-e PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True,max_split_size_mb:512 \
-e VLLM_FLOAT32_MATMUL_PRECISION=high \
-e VLLM_USE_FLASHINFER_SAMPLER=1 \
-e OMP_NUM_THREADS=1 \
-e CUDA_DEVICE_MAX_CONNECTIONS=8 \
-e CUDA_VISIBLE_DEVICES=0 \
-e CUDA_DEVICE_ORDER=PCI_BUS_ID \
-e VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 \
-e VLLM_MARLIN_USE_ATOMIC_ADD=1 \
-e GENESIS_ENABLE_P65_TURBOQUANT_SPEC_CG_DOWNGRADE=1 \
-e GENESIS_ENABLE_P66_CUDAGRAPH_SIZE_FILTER=1 \
-e GENESIS_ENABLE_P64_QWEN3CODER_MTP_STREAMING=1 \
-e GENESIS_ENABLE_P101=1 \
-e GENESIS_ENABLE_P103=1 \
-e GENESIS_ENABLE_PN12_FFN_INTERMEDIATE_POOL=1 \
-e GENESIS_ENABLE_PN13_CUDA_GRAPH_LAMBDA_ARITY=1 \
-e GENESIS_ENABLE_FA_MAX_SEQLEN_CLAMP=1 \
-e GENESIS_ENABLE_PN17_FA2_LSE_CLAMP=1 \
-v /mnt/ssd/vLLM/Models:/root/.cache/huggingface \
-v /mnt/ssd/vLLM/Patches/genesis/vllm/_genesis:/usr/local/lib/python3.12/dist-packages/vllm/_genesis:ro \
-v /mnt/ssd/vLLM/Patches/patch_tolist_cudagraph.py:/patches/patch_tolist_cudagraph.py:ro \
-v /mnt/ssd/vLLM/Patches/patch_pn12_ffn_pool_anchor.py:/patches/patch_pn12_ffn_pool_anchor.py:ro \
-v /mnt/ssd/vLLM/Patches/patch_pn12_compile_safe_custom_op.py:/patches/patch_pn12_compile_safe_custom_op.py:ro \
-v /mnt/ssd/vLLM/Patches/patch_fa_max_seqlen_clamp.py:/patches/patch_fa_max_seqlen_clamp.py:ro \
-v /mnt/ssd/vLLM/Patches/patch_timings_07351e088.py:/patches/patch_timings_07351e088.py:ro \
-p ''${PORT}:8000 \
--entrypoint /bin/bash \
vllm/vllm-openai:nightly-07351e0883470724dd5a7e9730ed10e01fc99d08 \
-c "${vllmCmdFlat}"
'';
cmdStop = "${pkgs.docker}/bin/docker stop \${MODEL_ID}";
metadata = {
type = [
"text-generation"
"coding"
"vision"
];
};
};
# https://github.com/noonghunna/club-3090/tree/master/models/qwen3.6-27b/vllm
# Tools-text variant - 75K context, text-only (no vision)
# fp8_e5m2 KV + MTP n=3. This is the repo's validated long-context
# tool-calling profile and should be more stable than TurboQuant 128K.
"vllm-qwen3.6-27b-tools-text" = {
name = "vLLM Qwen3.6 (27B) - Tools Text";
macros.ctx = "75000";
proxy = "http://127.0.0.1:\${PORT}";
cmd =
let
vllmCmd = ''
set -e; pip install xxhash pandas scipy -q;
python3 -m vllm._genesis.patches.apply_all;
python3 /patches/patch_tolist_cudagraph.py;
python3 /patches/patch_timings_07351e088.py;
exec vllm serve
--served-model-name ''${MODEL_ID}
--model /root/.cache/huggingface/qwen3.6-27b-autoround-int4
--quantization auto_round
--dtype float16
--tensor-parallel-size 1
--max-model-len ''${ctx}
--gpu-memory-utilization 0.97
--max-num-seqs 1
--max-num-batched-tokens 2048
--kv-cache-dtype fp8_e5m2
--language-model-only
--trust-remote-code
--reasoning-parser qwen3
--enable-auto-tool-choice
--tool-call-parser qwen3_coder
--enable-prefix-caching
--enable-chunked-prefill
--speculative-config '{\"method\":\"mtp\",\"num_speculative_tokens\":3}'
--host 0.0.0.0
--port 8000
'';
vllmCmdFlat = builtins.replaceStrings [ "\n" ] [ " " ] vllmCmd;
in
''
${pkgs.docker}/bin/docker run --rm --device=nvidia.com/gpu=all \
--name ''${MODEL_ID} \
--ipc=host \
-e VLLM_WORKER_MULTIPROC_METHOD=spawn \
-e NCCL_CUMEM_ENABLE=0 \
-e NCCL_P2P_DISABLE=1 \
-e VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS=1 \
-e VLLM_NO_USAGE_STATS=1 \
-e PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True,max_split_size_mb:512 \
-e VLLM_FLOAT32_MATMUL_PRECISION=high \
-e VLLM_USE_FLASHINFER_SAMPLER=1 \
-e OMP_NUM_THREADS=1 \
-e CUDA_DEVICE_MAX_CONNECTIONS=8 \
-e CUDA_VISIBLE_DEVICES=0 \
-e CUDA_DEVICE_ORDER=PCI_BUS_ID \
-e VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 \
-e VLLM_MARLIN_USE_ATOMIC_ADD=1 \
-e GENESIS_ENABLE_P64_QWEN3CODER_MTP_STREAMING=1 \
-e GENESIS_ENABLE_PN8_MTP_DRAFT_ONLINE_QUANT=1 \
-v /mnt/ssd/vLLM/Models:/root/.cache/huggingface \
-v /mnt/ssd/vLLM/Patches/genesis/vllm/_genesis:/usr/local/lib/python3.12/dist-packages/vllm/_genesis:ro \
-v /mnt/ssd/vLLM/Patches/patch_tolist_cudagraph.py:/patches/patch_tolist_cudagraph.py:ro \
-v /mnt/ssd/vLLM/Patches/patch_timings_07351e088.py:/patches/patch_timings_07351e088.py:ro \
-p ''${PORT}:8000 \
--entrypoint /bin/bash \
vllm/vllm-openai:nightly-07351e0883470724dd5a7e9730ed10e01fc99d08 \
-c "${vllmCmdFlat}"
'';
cmdStop = "${pkgs.docker}/bin/docker stop \${MODEL_ID}";
metadata = {
type = [
"text-generation"
"coding"
];
};
};
# ---------------------------------------
# ------------- GTX 1080 Ti -------------
# ---------------------------------------
# https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF/tree/main
"qwen3-8b-vision" = {
name = "Qwen3 Vision (8B) - Thinking";
macros.ctx = "60000";
env = [ "CUDA_VISIBLE_DEVICES=1" ];
cmd = ''
${llama-cpp}/bin/llama-server \
--port ''${PORT} \
-m /mnt/ssd/Models/Qwen3/Qwen3-VL-8B-Instruct-UD-Q4_K_XL.gguf \
--mmproj /mnt/ssd/Models/Qwen3/Qwen3-VL-8B-Instruct-UD-Q4_K_XL_mmproj-F16.gguf \
-c ''${ctx} \
--temp 0.7 \
--min-p 0.0 \
--top-p 0.8 \
--top-k 20 \
-ctk q8_0 \
-ctv q8_0 \
-fit off \
-dev CUDA0
'';
metadata = {
type = [
"text-generation"
"vision"
];
};
};
# https://huggingface.co/unsloth/Qwen3.5-9B-GGUF/tree/main
"qwen3.5-9b-thinking" = {
name = "Qwen3.5 (9B) - Thinking";
macros.ctx = "131072";
env = [ "CUDA_VISIBLE_DEVICES=1" ];
cmd = ''
${llama-cpp}/bin/llama-server \
--port ''${PORT} \
-m /mnt/ssd/Models/Qwen3.5/Qwen3.5-9B-IQ4_XS.gguf \
--mmproj /mnt/ssd/Models/Qwen3.5/Qwen3.5-9B-IQ4_XS_mmproj-F16.gguf \
-c ''${ctx} \
--temp 0.6 \
--top-p 0.95 \
--top-k 20 \
--min-p 0.0 \
-fit off \
-dev CUDA0
'';
metadata = {
type = [
"text-generation"
"coding"
"vision"
];
};
};
# https://huggingface.co/unsloth/Qwen3.5-4B-GGUF/tree/main
"qwen3.5-4b-thinking" = {
name = "Qwen3.5 (4B) - Thinking";
macros.ctx = "131072";
env = [ "CUDA_VISIBLE_DEVICES=1" ];
cmd = ''
${llama-cpp}/bin/llama-server \
--port ''${PORT} \
-m /mnt/ssd/Models/Qwen3.5/Qwen3.5-4B-IQ4_XS.gguf \
-c ''${ctx} \
--temp 0.6 \
--top-p 0.95 \
--top-k 20 \
--min-p 0.0 \
-fit off \
-dev CUDA0
'';
metadata = {
type = [
"text-generation"
];
};
};
# ---------------------------------------
# -------- RTX 3090 + GTX 1080 Ti -------
# ---------------------------------------
# https://huggingface.co/unsloth/Qwen3-Coder-Next-GGUF/tree/main
"qwen3-coder-next-80b-instruct" = {
name = "Qwen3 Coder Next (80B) - Instruct";
macros.ctx = "131072";
cmd = ''
${llama-cpp}/bin/llama-server \
--port ''${PORT} \
-m /mnt/ssd/Models/Qwen3/Qwen3-Coder-Next-UD-Q4_K_XL.gguf \
-c ''${ctx} \
--temp 1.0 \
--top-p 0.95 \
--min-p 0.01 \
--top-k 40 \
-fit off \
-ncmoe 19 \
-ts 78,22
'';
metadata = {
type = [
"text-generation"
"coding"
];
};
};
# ---------------------------------------
# ---------- Stable Diffussion ----------
# ---------------------------------------
"z-image-turbo" = {
name = "Z-Image-Turbo";
checkEndpoint = "/";
cmd = ''
${stable-diffusion-cpp}/bin/sd-server \
--listen-port ''${PORT} \
--diffusion-fa \
--diffusion-model /mnt/ssd/StableDiffusion/ZImageTurbo/z-image-turbo-Q8_0.gguf \
--vae /mnt/ssd/StableDiffusion/ZImageTurbo/ae.safetensors \
--llm /mnt/ssd/Models/Qwen3/Qwen3-4B-Instruct-2507-Q4_K_M.gguf \
--cfg-scale 1.0 \
--steps 8 \
--rng cuda
'';
metadata = {
type = [ "image-generation" ];
};
};
"qwen-image-edit-2511" = {
name = "Qwen Image Edit 2511";
checkEndpoint = "/";
cmd = ''
${stable-diffusion-cpp}/bin/sd-server \
--listen-port ''${PORT} \
--diffusion-fa \
--qwen-image-zero-cond-t \
--diffusion-model /mnt/ssd/StableDiffusion/QwenImage/qwen-image-edit-2511-Q5_K_M.gguf \
--vae /mnt/ssd/StableDiffusion/QwenImage/qwen_image_vae.safetensors \
--llm /mnt/ssd/Models/Qwen2.5/Qwen2.5-VL-7B-Instruct.Q4_K_M.gguf \
--lora-model-dir /mnt/ssd/StableDiffusion/QwenImage/Loras \
--cfg-scale 2.5 \
--sampling-method euler \
--flow-shift 3 \
--steps 20 \
--rng cuda
'';
metadata = {
type = [
"image-edit"
"image-generation"
];
};
};
"qwen-image-2512" = {
name = "Qwen Image 2512";
checkEndpoint = "/";
cmd = ''
${stable-diffusion-cpp}/bin/sd-server \
--listen-port ''${PORT} \
--diffusion-fa \
--diffusion-model /mnt/ssd/StableDiffusion/QwenImage/qwen-image-2512-Q5_K_M.gguf \
--vae /mnt/ssd/StableDiffusion/QwenImage/qwen_image_vae.safetensors \
--llm /mnt/ssd/Models/Qwen2.5/Qwen2.5-VL-7B-Instruct.Q4_K_M.gguf \
--lora-model-dir /mnt/ssd/StableDiffusion/QwenImage/Loras \
--cfg-scale 2.5 \
--sampling-method euler \
--flow-shift 3 \
--steps 20 \
--rng cuda
'';
metadata = {
type = [ "image-generation" ];
};
};
"chroma-radiance" = {
name = "Chroma Radiance";
checkEndpoint = "/";
cmd = ''
${stable-diffusion-cpp}/bin/sd-server \
--listen-port ''${PORT} \
--diffusion-fa --chroma-disable-dit-mask \
--diffusion-model /mnt/ssd/StableDiffusion/Chroma/chroma_radiance_x0_q8.gguf \
--t5xxl /mnt/ssd/StableDiffusion/Chroma/t5xxl_fp16.safetensors \
--cfg-scale 4.0 \
--sampling-method euler \
--rng cuda
'';
metadata = {
type = [ "image-generation" ];
};
};
};
# Concurrent Model Matrix
#
# CUDA0 models can run alongside CUDA1 models (one each). Models not
# listed in any set (dual-GPU models using -ts) run alone and evict
# everything.
matrix = {
vars = {
# --- RTX 3090 Models ---
vlt = "vllm-qwen3.6-27b-long-text";
vtt = "vllm-qwen3.6-27b-tools-text";
vlv = "vllm-qwen3.6-27b-long-vision";
go = "gpt-oss-20b-thinking";
q36a = "qwen3.6-35b-thinking";
q36b = "qwen3.6-27b-thinking";
zi = "z-image-turbo";
qie = "qwen-image-edit-2511";
qi = "qwen-image-2512";
cr = "chroma-radiance";
# --- GTX 1080 Ti Models ---
qv = "qwen3-8b-vision";
q4 = "qwen3.5-4b-thinking";
q9 = "qwen3.5-9b-thinking";
};
evict_costs = {
vlt = 50;
vtt = 50;
vlv = 50;
};
sets = {
concurrent = "(go | q36a | q36b | vlt | vtt | vlv | zi | qie | qi | cr) & (qv | q4 | q9)";
};
};
}
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