Large Language Models, Quiz 2
Consider the following dictionary with the number of word occurrences in a corpus:
wo = { "deeper": 5, "keener": 6, "sweeter": 7,}Note: Append identifier/special symbol </w> to each word at the end.
You will be learning a byte pair encoding, answer the given subquestions in that context:
How many tokens are there in the initial vocabulary?
Consider the following dictionary with the number of word occurrences in a corpus: wo = { "deeper": 5, "keener": 6, "sweeter": 7,} **Note:** Append identifier/special symbol </w> to each word at the end. You will be learning a byte pair encoding, answer the given subquestions in that context: How many tokens are there in the initial vocabulary? Consider the following dictionary with the number of word occurrences in a corpus: wo = { "deeper": 5, "keener": 6, "sweeter": 7,} **Note:** Append identifier/special symbol </w> to each word at the end. You will be learning a byte pair encoding, answer the given subquestions in that context: Which of the following pairs has the least frequency before any merge? Consider the following dictionary with the number of word occurrences in a corpus: wo = { "deeper": 5, "keener": 6, "sweeter": 7,} **Note:** Append identifier/special symbol </w> to each word at the end. You will be learning a byte pair encoding, answer the given subquestions in that context: What is the most frequent byte-pair before the very first merge? Say the most frequent byte pair is (‘a’,‘b’), then enter **“ab”** (without quotes and white spaces). If there is a tie between two or more candidates, pick the one that occurs first in the original vocabulary.