NCA-GENM exam dumps

NCA-GENM practice question 52 of 228

NVIDIA-Certified Associate - Generative AI Multimodal. Associate level, NVIDIA. Free question with the correct answer and a full explanation.

NCA-GENM Question 52

Select 3

You are tasked with building a multimodal generative AI model that combines image and text modalities. The development involves selecting a deep learning framework. Which of the following features of TensorFlow and PyTorch make them suitable for this task?

  1. A

    Both frameworks support dynamic computation graphs for flexible model definition.

  2. B

    PyTorch has advanced support for ONNX (Open Neural Network Exchange) to optimize multimodal models for deployment.

  3. C

    TensorFlow offers pre-built modules like TensorFlow Hub for easy integration of multimodal models.

  4. D

    Both frameworks provide native support for multi-GPU training, which is essential for large multimodal datasets.

  5. E

    Neither TensorFlow nor PyTorch supports integration with pre-trained vision and language models.

Show answer and explanation

Correct answers: B, C, D

Explanation

TensorFlow and PyTorch are widely used deep learning frameworks for multimodal generative AI tasks. PyTorch's ONNX support ensures smooth deployment of models, while TensorFlow Hub simplifies access to pre-trained modules. Both frameworks excel in handling multi-GPU training, a critical feature for training large-scale multimodal datasets. These features make them suitable choices for implementing and deploying complex multimodal AI models.

  • A. Incorrect.

    Incorrect: While PyTorch supports dynamic computation graphs, TensorFlow primarily uses static graphs with eager execution for flexibility. This statement is partially correct but not exclusive to both frameworks.

  • B. Correct.

    Correct: PyTorch has strong ONNX support, enabling efficient deployment of multimodal AI models across platforms, which is critical for production use cases.

  • C. Correct.

    Correct: TensorFlow Hub provides an excellent repository of pre-built modules, including multimodal models, which simplifies model integration and implementation.

  • D. Correct.

    Correct: Both TensorFlow and PyTorch support multi-GPU training out of the box, which is essential for training resource-intensive multimodal models on large datasets.

  • E. Incorrect.

    Incorrect: Both frameworks support integration with pre-trained models for vision and language tasks, making this statement factually incorrect.

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