106. Which of the following is a technique used to generate text using GPT?
a) Sampling
b) Gradient descent
c) Backpropagation
d) Regularization
107. What is the difference between autoregressive and non-autoregressive language models?
a) Autoregressive models generate one token at a time, while non-autoregressive models generate multiple tokens at once.
b) Autoregressive models can generate text in any order, while non-autoregressive models must generate text sequentially.
c) Autoregressive models can generate variable-length sequences, while non-autoregressive models generate fixed-length sequences.
d) Autoregressive models use the previous tokens to predict the next token, while non-autoregressive models do not.
108. Which of the following is a technique used to improve the diversity of text generated by GPT?
a) Beam search
b) Greedy decoding
c) Top-k sampling
d) Top-p sampling
109. What is the difference between zero-shot and few-shot learning?
a) Zero-shot learning involves training a model on a large amount of data, while few-shot learning involves training a model on a small amount of data.
b) Zero-shot learning involves training a model on one task and evaluating it on another, while few-shot learning involves training a model on a small amount of data for a specific task.
c) Zero-shot learning is used for unsupervised learning, while few-shot learning is used for supervised learning.
d) Zero-shot learning is used for classification tasks, while few-shot learning is used for regression tasks.
110. What is the purpose of the GPT-X series of models?
a) To improve the accuracy and efficiency of GPT models.
b) To generate more diverse and creative text.
c) To train models on larger amounts of data.
d) To improve the model’s ability to understand context.
