Repository: open-compass/opencompass
Issue: [Bug]  测试用例数据集Winograd失败
Root cause: Documentation Deficiency

### 描述该错误

根据Docs中的demo示例，测试在 [SIQA](https://huggingface.co/datasets/social_i_qa) 和 [Winograd](https://huggingface.co/datasets/winogrande) 这两个数据，其中Winograd数据集与本地dataset代码不兼容，跑不通，注释掉即可正常使用，希望进行排查
![image](https://github.com/InternLM/opencompass/assets/40393969/a22f1f49-fb92-4130-8bc3-6efa52a6e640)
即使把这里的名字改为‘winogrande_xl’，又会报其他错，把这数据注释掉，就没有问题
![image](https://github.com/InternLM/opencompass/assets/40393969/700284e0-4407-4b06-8503-0b91b4dec5a1)


### 环境信息

{'CUDA available': True,
 'CUDA_HOME': '/usr/local/cuda-11.1',
 'GCC': 'gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-44)',
 'GPU 0,1,2,3': 'NVIDIA GeForce RTX 3090',
 'MMEngine': '0.8.2',
 'NVCC': 'Cuda compilation tools, release 11.1, V11.1.74',
 'OpenCV': '4.8.0',
 'PyTorch': '2.0.1',
 'PyTorch compiling details': 'PyTorch built with:\n'
                              '  - GCC 9.3\n'
                              '  - C++ Version: 201703\n'
                              '  - Intel(R) oneAPI Math Kernel Library Version '
                              '2023.1-Product Build 20230303 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 11.8\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_61,code=sm_61;-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;-gencode;arch=compute_37,code=compute_37\n'
                              '  - CuDNN 8.7\n'
                              '  - Magma 2.6.1\n'
                              '  - Build settings: BLAS_INFO=mkl, '
                              'BUILD_TYPE=Release, CUDA_VERSION=11.8, '
                              'CUDNN_VERSION=8.7.0, '
                              '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=2.0.1, 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=ON, USE_NNPACK=ON, '
                              'USE_OPENMP=ON, USE_ROCM=OFF, \n',
 'Python': '3.10.12 (main, Jul  5 2023, 18:54:27) [GCC 11.2.0]',
 'TorchVision': '0.15.2',
 'numpy_random_seed': 2147483648,
 'opencompass': '0.1.0+',
 'sys.platform': 'linux'}

### 其他信息

_No response_

It's not a bug. You have changed the dataset path to winogrand**e** instead of `winogrand_wsc`: https://huggingface.co/datasets/winograd_wsc 

好的，非常感谢~！我依据Docs中给出的[Winograd](https://huggingface.co/datasets/winogrande)路径下载的数据，导致了这个错误，这里链接指向了winogrande，而不是winograd_wsc

> 好的，非常感谢~！我依据Docs中给出的[Winograd](https://huggingface.co/datasets/winogrande)路径下载的数据，导致了这个错误，这里链接指向了winogrande，而不是winograd_wsc

看你上面的代码，是将winograd的数据下载到了你本地，path是一个本地路径，请问下，你是如何将https://huggingface.co/datasets/winograd_wsc 这个数据下载的本地呢？
对于在线数据，我现在都是使用联网的服务器load到.cache中，然后将.cache拷贝到不能上网的服务器上使用

你这里是如何操作的呢？感谢。

可以像clone HG模型一样，直接git clone https://huggingface.co/datasets/winograd_wsc。