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spark-vllm-docker/recipes/4x-spark-cluster/minimax-m2.5.yaml

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YAML

# Recipe: MiniMax-M2.5
# MiniMaxAI/MiniMax-M2.5
recipe_version: "1"
name: MiniMax-M2.5
description: vLLM serving MiniMax-M2.5 with Ray distributed backend
# HuggingFace model to download (optional, for --download-model)
model: MiniMaxAI/MiniMax-M2.5
# Container image to use
container: vllm-node
# Can only be run in a cluster
cluster_only: true
# No mods required
mods: []
# Default settings (can be overridden via CLI)
defaults:
port: 8000
host: 0.0.0.0
tensor_parallel: 4
gpu_memory_utilization: 0.90
max_model_len: 128000
# Environment variables
env:
VLLM_DISTRIBUTED_EXECUTOR_CONFIG: '{"placement_group_options":{"strategy":"SPREAD"}}'
# The vLLM serve command template
command: |
vllm serve MiniMaxAI/MiniMax-M2.5 \
--trust-remote-code \
--port {port} \
--host {host} \
--gpu-memory-utilization {gpu_memory_utilization} \
-tp {tensor_parallel} \
--distributed-executor-backend ray \
--max-model-len {max_model_len} \
--load-format fastsafetensors \
--enable-auto-tool-choice \
--tool-call-parser minimax_m2 \
--reasoning-parser minimax_m2_append_think