Miniforge enables installing python packages natively compiled for Apple Silicon.Īfter the installation of miniforge, by default, it gives us one base environment. Install miniforge for arm64 (Apple Silicon) from miniforge GitHub. xcode-select -install Step2: Install Miniforge If it’s not already installed in your system, you can install it by running the following command below in your terminal. I have already installed Xcode Command Line Tools on my mac. Step6: Run a Benchmark by training the MNIST dataset.Step5: Install Jupyter Notebook, Pandas.Step4: Install Tensorflow 2.5 and its dependencies.Step3: Create a virtual environment with python3.8.Here are the things that we are going to do. Here are the setup instructions for Tensorflow.Īt this time of writing Apple has released its Tensorflow 2.5 for Apple Silicon.īefore jumping into, I hope Homebrew is already installed in your system if not you can install it by running the following in your terminal /bin/bash -c “$(curl -fsSL )" I wanted to set up and test how machine learning frameworks are working in this new chip. Recently only some months back, I bought myself an M1 Macbook Pro with 8Gigs of RAM and 512GB of SSD. It got a lot of attention from everyone.īeing a tech enthusiast and a programmer, I was amazed to see the performance of the new apple M1 chip. Last year in November 2020 apple releases their first ARM64-based M1 chip.
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