NCA-GENL Question 187
Select 3You are a junior developer tasked with implementing a Python script to preprocess text data for training a large language model (LLM). Under the guidance of a senior team member, they suggest you focus specifically on tokenization and removing special characters. Which of the following steps should you include in your script to meet these requirements?
- A
Use a tokenizer library, such as Hugging Face's Tokenizer, to split text into tokens.
- B
Write a custom function to remove special characters like punctuation and symbols from the text.
- C
Implement a spell-checking algorithm to correct typos in the text.
- D
Compress the text data to reduce its overall size before tokenization.
- E
Ensure the tokenized text output maintains the order of words from the original text.
Show answer and explanation
Correct answers: A, B, E
Explanation
The task requires you to focus on tokenization and removing special characters as preprocessing steps for training an LLM. Tokenization ensures the text is split into manageable units, while removing special characters enhances data cleanliness. Maintaining the order of words in the tokenized output is also crucial for preserving the integrity of the original text. Other options, like spell-checking or compressing data, are not relevant to the specific requirements provided by the senior team member.
- A. Correct.
Using a tokenizer library is an essential and efficient method for tokenizing text, which is a key requirement of the task.
- B. Correct.
Removing special characters is explicitly mentioned in the task requirements and is a necessary preprocessing step.
- C. Incorrect.
While spell-checking can improve data quality, it is not mentioned as part of the specific requirements for this task.
- D. Incorrect.
Compressing the text is not relevant to the preprocessing steps of tokenization or removing special characters.
- E. Correct.
Maintaining word order in the tokenized output is important for preserving the context and meaning of the original text, aligning with the requirements.