I adapted it from my docker image, in case you are using Linux directly:
https://github.com/QuantScientist/Deep-Learning-Boot-Camp/blob/master/day%2002%20PyTORCH%20and%20PyCUDA/PyTorch/build_torch.sh
# PyTorch GPU and CPU
# If you dont have CUDA installed, run this first:
# https://github.com/QuantScientist/Deep-Learning-Boot-Camp/blob/master/docker/deps_nvidia_docker.sh
#GPU version
export PATH=/usr/local/cuda-8.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
export PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
export CUDA_BIN_PATH=/usr/local/cuda
export CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-8.0
# Build PyTorch from source
#git clone https://github.com/pytorch/pytorch.git
cd pytorch
git submodule update --init
#git checkout 4eb448a051a1421de1dda9bd2ddfb34396eb7287
export TORCH_CUDA_ARCH_LIST="3.5 5.2 6.0 6.1+PTX"
export TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
#pip uninstall torch
#python setup.py clean
#python setup.py build
python setup.py install
# Build torch-vision from source
git clone https://github.com/pytorch/vision.git
cd vision
#git checkout 83263d8571c9cdd46f250a7986a5219ed29d19a1
git submodule update --init
python setup.py install
# CPU version
#pip install git+https://github.com/pytorch/tnt.git@master