How to install tensorflow-text on Mac M1/M2 | by Lakshmi Priya Ramisetty | Mar, 2024


TensorFlow-Text is an essential library for natural language processing (NLP) tasks in the TensorFlow ecosystem. However, installing TensorFlow-Text on the Apple Silicon (M1/M2) Macs can be a bit tricky due to the ARM architecture.

This guide provides a clear, step-by-step approach to get TensorFlow-Text up and running on your Mac M1/M2.

Before you start, ensure you have:

  1. Python: TensorFlow requires Python 3.6–3.9. Python 3.8 is recommended for the best compatibility with other libraries.
  2. Homebrew: This package manager for macOS simplifies the installation of other tools.
  3. Virtual Environment: It’s good practice to use a virtual environment to manage dependencies.

If you haven’t installed Python, you can do so via Homebrew:

brew install python@3.9

If you have python already installed, you can find the version of your python using this command:

python --version

Install TensorFlow using pip:

pip install tensorflow

If you have TensorFlow already installed, you can find the version of your TensorFlow using this command:

import tensorflow as tf
print("TensorFlow version:", tf.__version__)

Ensure you have the specific version numbers for Python and TensorFlow before proceeding. With these details, you can select and download the appropriate tensorflow-text file from this repository — https://github.com/sun1638650145/Libraries-and-Extensions-for-TensorFlow-for-Apple-Silicon/releases

After downloading the file, install it using the following command:

pip install "path-to-your-downloaded-whl"

Example Usage:

pip install /Users/laasya/Downloads/tensorflow_text-2.16.1-cp39-cp39-macosx_11_0_arm64.whl

Installing TensorFlow-Text on an Apple Silicon Mac might seem daunting at first, but by following these steps, you can set up a robust environment for your NLP projects.



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