[Bug]: docker容器版本的sglang不支持minicpm3-4b

[cicicji]

Is there an existing issue ? / 是否已有相关的 issue ?

• [X] I have searched, and there is no existing issue. / 我已经搜索过了，没有相关的 issue。

Describe the bug / 描述这个 bug

Model architectures ['MiniCPM'] are not supported for now. Supported architectures: ['AquilaModel', 'AquilaForCausalLM', 'BaiChuanForCausalLM', 'BaichuanForCausalLM', 'BloomForCausalLM', 'ChatGLMModel', 'ChatGLMForConditionalGeneration', 'CohereForCausalLM', 'DbrxForCausalLM', 'DeciLMForCausalLM', 'DeepseekForCausalLM', 'DeepseekV2ForCausalLM', 'ExaoneForCausalLM', 'FalconForCausalLM', 'GemmaForCausalLM', 'Gemma2ForCausalLM', 'GPT2LMHeadModel', 'GPTBigCodeForCausalLM', 'GPTJForCausalLM', 'GPTNeoXForCausalLM', 'InternLMForCausalLM', 'InternLM2ForCausalLM', 'JAISLMHeadModel', 'LlamaForCausalLM', 'LLaMAForCausalLM', 'MistralForCausalLM', 'MixtralForCausalLM', 'QuantMixtralForCausalLM', 'MptForCausalLM', 'MPTForCausalLM', 'MiniCPMForCausalLM', 'NemotronForCausalLM', 'OlmoForCausalLM', 'OPTForCausalLM', 'OrionForCausalLM', 'PersimmonForCausalLM', 'PhiForCausalLM', 'Phi3ForCausalLM', 'PhiMoEForCausalLM', 'QWenLMHeadModel', 'Qwen2ForCausalLM', 'Qwen2MoeForCausalLM', 'RWForCausalLM', 'StableLMEpochForCausalLM', 'StableLmForCausalLM', 'Starcoder2ForCausalLM', 'ArcticForCausalLM', 'XverseForCausalLM', 'Phi3SmallForCausalLM', 'MedusaModel', 'EAGLEModel', 'MLPSpeculatorPreTrainedModel', 'JambaForCausalLM', 'GraniteForCausalLM', 'MistralModel', 'Blip2ForConditionalGeneration', 'ChameleonForConditionalGeneration', 'FuyuForCausalLM', 'InternVLChatModel', 'LlavaForConditionalGeneration', 'LlavaNextForConditionalGeneration', 'MiniCPMV', 'PaliGemmaForConditionalGeneration', 'Phi3VForCausalLM', 'UltravoxModel', 'BartModel', 'BartForConditionalGeneration']

To Reproduce / 如何复现

docker run --name vllm-minicpm3-4b --runtime nvidia --gpus '"device=0,1"' -v /home/jszc/vllm:/root/.cache/modelscope -p 11436:8080 --ipc=host my_vllm_updated:latest --model /root/.cache/modelscope/MiniCPM3-4B --port=8080 --served-model-name llama3.1-8b --gpu-memory-utilization 0.95 --max_num_seqs 1024 --max_num_batched_tokens 8192 -tp 2 --enable-chunked-prefill true --enable-prefix-caching --trust-remote-code

Expected behavior / 期望的结果

No response

Screenshots / 截图

No response

Environment / 环境

- OS: [e.g. Ubuntu 20.04]
- Pytorch: [e.g. torch 2.0.0]
- CUDA: [e.g. CUDA 11.8]
- Device: [e.g. A10, RTX3090]

Additional context / 其他信息

No response