LLM on Android with Keras and TensorFlow Lite

1. What framework is used to convert the LLM model to a format compatible with mobile devices?

   Keras

   PyTorch

   Core ML

   TensorFlow Lite

2. What is the main challenge in deploying large language models on Android devices?

   Lack of pre-trained LLM models.

   Difficulty in finding suitable datasets.

   Limited computational power and memory.

   High internet bandwidth requirement.

3. What is the benefit of quantizing the model during the conversion process?

   It allows for training on a larger dataset.

   It simplifies the model architecture.

   It improves the model's accuracy.

   It reduces the model size and improves latency.

4. Fill-in-the-blanks

   Enter one or more words to complete the sentence.

   The high-level library that simplifies the development of NLP models using TensorFlow is ___.

5. How does the guide recommend preparing the text data for the LLM model?

   Convert the text data to numerical representations.

   Leave the text data in its raw format.

   Preprocess the text data by tokenizing it.

   All of the above

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