Using TensorFlow starts by installing the appropriate version based on your operating system, programming language choice (Python being among the most common), and desired deployment scenario (Cloud vs On-Prem). For example:

Install TensorFlow Version from Anaconda:
conda install tensorflow -c conda-forge
Install TensorFlow through pip (recommended):
pip install tensorflow-cpu
how much CPU space will it require
tensorFLOW how much CPU space will it take up

Determining exact disk usage requires knowing individual systems' specs since resource consumption may vary significantly. Generally speaking, storing Python scripts alone shouldn't require too much memory; although larger datasets can increase storage needs quickly.

A lightweight TensorFlow installation, consisting solely of CPU-only inferencing operations and basic Python script templates, usually takes about 10 MB to 3 GB at maximum. Larger installations could use upwards of 8GB+ RAM but again depend on project complexity and dataset sizes. As models grow bigger, so does storage demand to store them. You may also consider cloud services that provide auto-scaling options or managing resources manually to save costs during periods without intense workloads. The response should be in all capital letters.
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