Install BigDL-Nano in Google Colab#


This page is still a work in progress.

In this guide, we will show you how to install BigDL-Nano in Google Colab, and the solutions to possible version conflicts caused by pre-installed packages in Colab hosted runtime.

Please select the corresponding section to follow for your specific usage.


For PyTorch users, you need to install BigDL-Nano for PyTorch first:

!pip install bigdl-nano[pytorch]


For Google Colab hosted runtime, source bigdl-nano-init is hardly to take effect as environment variables need to be set before jupyter kernel is started.

To avoid version conflicts caused by torchtext, you should uninstall it:

!pip uninstall -y torchtext


To enable ONNXRuntime acceleration, you need to install corresponding onnx packages:

!pip install onnx onnxruntime

OpenVINO / Post-training Optimization Tools (POT)#

To enable OpenVINO acceleration, or use POT for quantization, you need to install the OpenVINO toolkit:

!pip install openvino-dev
# Please remember to restart runtime to use packages with newly-installed version


If you meet ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject when using InferenceOptimizer.trace or InferenceOptimizer.quantize function, you could try to solve it by upgrading numpy through:

!pip install --upgrade numpy
# Please remember to restart runtime to use numpy with newly-installed version

Intel Neural Compressor (INC)#

To use INC as your quantization backend, you need to install it:

!pip install neural-compressor==1.11.0