File size: 1,442 Bytes
dd138ec | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | #!/bin/bash
# Launch vLLM server for mistralai/Magistral-Small-2509.
#
# Hardware: 2× L40S 48GB (TP=2).
# Default port: 8004. Override with PORT env var.
#
# Key settings:
# --tokenizer-mode mistral \
# --config-format mistral \
# --load-format mistral — Mistral models require their own tokenizer/loader
# --tool-call-parser mistral — uses Mistral tool-call format
# --reasoning-parser mistral — strips Magistral thinking tokens
# tool_choice=auto — Magistral returns empty tool_calls with 'required';
# 'auto' is the correct setting for this model
set -euo pipefail
HF_HUB_CACHE="${HF_HUB_CACHE:-/data/hf_cache/hub}"
export HF_HUB_CACHE
VENV="${SAFEMASS_VENV:-$(dirname "$0")/../.venv}"
PORT="${PORT:-8004}"
LOGS="${LOGS_DIR:-/tmp/vllm_logs}"
mkdir -p "$LOGS"
CUDA_VISIBLE_DEVICES="${CUDA_VISIBLE_DEVICES:-3,4}" \
"${VENV}/bin/python3" -m vllm.entrypoints.openai.api_server \
--model mistralai/Magistral-Small-2509 \
--tensor-parallel-size 2 \
--max-model-len 16384 \
--gpu-memory-utilization 0.90 \
--port "$PORT" \
--host 127.0.0.1 \
--trust-remote-code \
--tokenizer-mode mistral \
--config-format mistral \
--load-format mistral \
--enable-auto-tool-choice \
--tool-call-parser mistral \
--reasoning-parser mistral \
--no-scheduler-reserve-full-isl \
>> "${LOGS}/vllm_magistral_${PORT}.log" 2>&1
|