Repository: open-compass/opencompass
Issue: Tried to download gsm8K locally and run the test but fail[Bug] 
Root cause: Documentation Deficiency

### Prerequisite

- [X] I have searched [Issues](https://github.com/open-compass/opencompass/issues/) and [Discussions](https://github.com/open-compass/opencompass/discussions) but cannot get the expected help.
- [X] The bug has not been fixed in the [latest version](https://github.com/open-compass/opencompass).

### Type

I'm evaluating with the officially supported tasks/models/datasets.

### Environment

{'CUDA available': True,
 'CUDA_HOME': '/usr/local/cuda',
 'GCC': 'gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0',
 'GPU 0': 'NVIDIA A100-SXM4-80GB',
 'MMEngine': '0.8.5',
 'NVCC': 'Cuda compilation tools, release 11.8, V11.8.89',
 'OpenCV': '4.8.1',
 'PyTorch': '2.0.0+cu117',
 'PyTorch compiling details': 'PyTorch built with:\n'
                              '  - GCC 9.3\n'
                              '  - C++ Version: 201703\n'
                              '  - Intel(R) oneAPI Math Kernel Library Version '
                              '2022.2-Product Build 20220804 for Intel(R) 64 '
                              'architecture applications\n'
                              '  - Intel(R) MKL-DNN v2.7.3 (Git Hash '
                              '6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e)\n'
                              '  - OpenMP 201511 (a.k.a. OpenMP 4.5)\n'
                              '  - LAPACK is enabled (usually provided by '
                              'MKL)\n'
                              '  - NNPACK is enabled\n'
                              '  - CPU capability usage: AVX2\n'
                              '  - CUDA Runtime 11.7\n'
                              '  - NVCC architecture flags: '
                              '-gencode;arch=compute_37,code=sm_37;-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\n'
                              '  - CuDNN 8.5\n'
                              '  - Magma 2.6.1\n'
                              '  - Build settings: BLAS_INFO=mkl, '
                              'BUILD_TYPE=Release, CUDA_VERSION=11.7, '
                              'CUDNN_VERSION=8.5.0, '
                              'CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, '
                              'CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 '
                              '-fabi-version=11 -Wno-deprecated '
                              '-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 -Wunused-local-typedefs '
                              '-Wno-unused-parameter -Wno-unused-function '
                              '-Wno-unused-result -Wno-strict-overflow '
                              '-Wno-strict-aliasing '
                              '-Wno-error=deprecated-declarations '
                              '-Wno-stringop-overflow -Wno-psabi '
                              '-Wno-error=pedantic -Wno-error=redundant-decls '
                              '-Wno-error=old-style-cast '
                              '-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=2.0.0, 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, \n',
 'Python': '3.10.0 (default, Mar  3 2022, 09:58:08) [GCC 7.5.0]',
 'TorchVision': '0.15.1+cu117',
 'numpy_random_seed': 2147483648,
 'opencompass': '0.1.5+',
 'sys.platform': 'linux'}

### Reproduces the problem - code/configuration sample

I tried to download the gsm8k locally to the data folder. Then I have no idea where to modify the model path so that it could skip the hf download part and go straight into eval based on my local file. Tried to modify the gsm8k_datasets path, but it seems not working at all. It goes to the HF download. I think it is for the type being defined as HFDataset. Please show me how to do it. Thanks~

Plus: my cloud network isn't working so have to use a local file

![Screen Shot 2023-10-10 at 11 55 11 AM](https://github.com/open-compass/opencompass/assets/44200118/37d9fa41-bec6-4a1c-970d-50ea18211603)

### Reproduces the problem - command or script

![Screen Shot 2023-10-10 at 12 00 04 PM](https://github.com/open-compass/opencompass/assets/44200118/998763c4-1559-426d-b609-59ca3afce07d)


### Reproduces the problem - error message

xxx

### Other information

_No response_

So the question is where to put the downloaded gsm8k data and config the path so that I can run the config python file to start the eval process. Cheers.