Model name id returned is weird specially when using Docker [Bug]

### Checklist

- [X] 1. I have searched related issues but cannot get the expected help.
- [X] 2. The bug has not been fixed in the latest version.

### Describe the bug

Hi!
When using the cli command:
lmdeploy serve api_server OpenGVLab/InternVL-Chat-V1-5-AWQ --backend turbomind --model-format awq
the model name returned by the API (v1/models) is: internvl-internlm2

Shouldn't it be: OpenGVLab/InternVL-Chat-V1-5-AWQ ???

But when I run the same service via docker with the following Docker command, the ID returned gets weirder:

dockerfile:
---------------------------------------
FROM openmmlab/lmdeploy:latest

RUN apt-get update && apt-get install -y python3 python3-pip git
WORKDIR /app

RUN pip3 install --upgrade pip
RUN pip3 install timm
RUN pip3 install flash-attn --no-build-isolation

CMD ["lmdeploy", "serve", "api_server", "OpenGVLab/InternVL-Chat-V1-5-AWQ", "--backend", "turbomind", "--model-format", "awq"]
---------------------------------------
docker build --tag 'lmdeploy' .
----------------------------------------
docker run --privileged --runtime nvidia --gpus all -v ~/.cache/huggingface:/root/.cache/huggingface --env "HUGGING_FACE_HUB_TOKEN=" -p 23333:23333 --ipc=host lmdeploy lmdeploy serve api_server OpenGVLab/InternVL-Chat-V1-5-AWQ
-----------------------------------------

then when I try the API, the ID returned is the following:
/root/.cache/huggingface/hub/models--OpenGVLab--InternVL-Chat-V1-5-AWQ/snapshots/5ce4e49fe4e5d960b62a619b268113e40943c57f

As this Id is used in the web UI I'm using to show the model name, I'd rather have the normal short name, but while using Docker.

### Reproduction

1.start lmdeploy using Docker recipe above
2.open browser to check fast api web page (http://{serverIP}:23333)
3.test the GET v1/models endpoint
4.Notice that the object.data[0].id is not the normal short name

### Environment

```Shell
sys.platform: linux
Python: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0: NVIDIA RTX A6000
CUDA_HOME: /usr
NVCC: Cuda compilation tools, release 11.5, V11.5.119
GCC: x86_64-linux-gnu-gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
PyTorch: 2.1.0+cu121
PyTorch compiling details: PyTorch built with:
- GCC 9.3
- C++ Version: 201703
- Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v3.1.1 (Git Hash 64f6bcbcbab628e96f33a62c3e975f8535a7bde4)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 12.1
- NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90
- CuDNN 8.9.2
- Magma 2.6.1
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=12.1, CUDNN_VERSION=8.9.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-invalid-partial-specialization -Wno-unused-private-field -Wno-aligned-allocation-unavailable -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.1.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

TorchVision: 0.16.0+cu121
LMDeploy: 0.4.2+
transformers: 4.36.2
gradio: 4.36.1
fastapi: 0.111.0
pydantic: 2.7.4
triton: 2.1.0
```

### Error traceback

_No response_