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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is data collection in the context of training language models?
💡 Hint: Think of where the model gets its information.
Question 2
Easy
Define tokenization.
💡 Hint: It's like cutting a sentence into smaller parts.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the purpose of tokenization in training language models?
- To collect data
- To divide text into smaller units
- To evaluate the model
💡 Hint: Think about the process of making data manageable.
Question 2
True or False: Fine-tuning helps align a model's responses with human expectations.
- True
- False
💡 Hint: Consider how feedback can change one’s work.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a training pipeline for a new language model, including strategies for each step from data collection to RLHF.
💡 Hint: Think about each step's contribution to the model’s capability.
Question 2
Analyze how insufficient data collection may impact the performance of a language model. What steps could be taken to mitigate this issue?
💡 Hint: Consider the consequences of having a limited view versus a comprehensive one.
Challenge and get performance evaluation