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AI0-001 AI Infrastructure and Technologies Practice Question

A developer is building a mobile app that uses a pre-trained image classification model on-device. Which framework should they use to run the model on iOS devices?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Core ML

Core ML is Apple's framework for on-device machine learning inference on iOS. TensorFlow Lite is for mobile and embedded, but Core ML is native to iOS and optimized.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Hugging Face Transformers

    Why it's wrong here

    Hugging Face is for NLP models, not specifically for iOS image classification.

  • TensorFlow Lite

    Why it's wrong here

    TensorFlow Lite is cross-platform but not native to iOS; Core ML is optimized for Apple hardware.

  • PyTorch Mobile

    Why it's wrong here

    PyTorch Mobile supports Android and iOS, but Core ML is more integrated for iOS.

  • Core ML

    Why this is correct

    Core ML is Apple's native framework for on-device ML inference on iOS devices.

About these practice questions

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.