NCA-GENL Practice Test

NCA-GENL Practice Test practice questions, page 4 of 4, with answer review and explanations.

Question 16

Which of the following is a parameter-efficient fine-tuning approach that one can use to fine-tune LLMs in a memory efficient fashion?

  1. Tensor-RT
  2. NEMO
  3. Chinchilla
  4. LoRA

Question 17

Which library is used to accelerate data preparation operations on the GPU?

  1. cuML
  2. XGBoost
  3. cuDF
  4. cuGraph

Question 18

When fine-tuning an LLM for a specific application, why is it essential to perform exploratory data analysis (EDA) on the new training dataset?

  1. To assess the computing resources required for fine-tuning
  2. To uncover patterns and anomalies in the dataset
  3. To select the appropriate learning rate for the model
  4. To determine the optimum number of layers in the neural network

Question 19

Why might stemming or lemmatizing text be considered a beneficial preprocessing step in the context of computing TF-IDF vectors for a corpus?

  1. It reduces the number of unique tokens by collapsing variant forms of a word into their root form, potentially decreasing noise in the data.
  2. It enhances the aesthetic appeal of the text, making it easier for readers to understand the document’s content.
  3. It increases the complexity of the dataset by introducing more unique tokens, enhancing the distinctiveness of each document.
  4. It guarantees an increase in the accuracy of TF-IDF vectors by ensuring more precise word usage distinction.