
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:
- Python: TensorFlow requires Python 3.6–3.9. Python 3.8 is recommended for the best compatibility with other libraries.
- Homebrew: This package manager for macOS simplifies the installation of other tools.
- 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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