
Instruction Fine-Tuning in Language Models

Interactive Video
•
Computers, Education, Instructional Technology
•
10th Grade - University
•
Hard

Emma Peterson
FREE Resource
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10 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary purpose of instruction fine-tuning in language models?
To improve the model's grammar
To teach the model to follow human instructions
To increase the model's vocabulary
To enhance the model's speed
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is it not sufficient to train language models solely with human-prepared data?
Human data is too expensive
Human data is too complex
Human data is too simple
Human data is limited in scope
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the role of pre-trained parameters in the second phase of language model training?
They serve as initial parameters
They are discarded
They are used for testing
They are ignored
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How do adapters like LoRA contribute to the fine-tuning process?
By changing the model's architecture
By increasing the number of parameters
By simplifying the data
By reducing the computational load
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What advantage does pre-training provide to language models?
It simplifies the model's rules
It allows the model to learn complex rules
It limits the model's capabilities
It reduces the model's size
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main challenge in creating a general-purpose language model?
Collecting enough data for every possible task
Ensuring the model is specialized for one task
Reducing the size of the model
Increasing the speed of the model
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which model was used in early experiments before the release of GPT-3?
GPT-2
FLAN
T0
Llama
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