| # [ragqa] vLLM OpenAI 兼容服务(端口 50001):Llama 基座 + 监督式分解 LoRA | |
| # 需要环境变量:RAGQA_LLAMA_MODEL(基座目录);RAGQA_LLAMA_LORA_SUPERVISED(监督式 LoRA,可选) | |
| export CUDA_VISIBLE_DEVICES=${CUDA_VISIBLE_DEVICES:-0,1,2,3} | |
| : "${RAGQA_LLAMA_MODEL:?请先设置 RAGQA_LLAMA_MODEL 指向 Llama-3.1-8B-Instruct 目录}" | |
| ARGS=( | |
| --model "$RAGQA_LLAMA_MODEL" | |
| --tensor_parallel_size "${RAGQA_TP_SIZE:-4}" | |
| --gpu_memory_utilization 0.6 | |
| --port 50001 | |
| --max-num-seqs 256 | |
| --max-model-len 4096 | |
| --use-v2-block-manager | |
| --disable-log-requests | |
| ) | |
| if [ -n "$RAGQA_LLAMA_LORA_SUPERVISED" ]; then | |
| ARGS+=(--enable-lora --max-lora-rank 64 | |
| --lora-modules "{\"name\": \"supervised\", \"path\": \"$RAGQA_LLAMA_LORA_SUPERVISED\", \"base_model_name\": \"$RAGQA_LLAMA_MODEL\"}") | |
| fi | |
| python -m vllm.entrypoints.openai.api_server "${ARGS[@]}" | |