ExamGecko
Question list
Search
Search

Question 21 - D-GAI-F-01 discussion

Report
Export

What is P-Tuning in LLM?

A.
Adjusting prompts to shape the model's output without altering its core structure
Answers
A.
Adjusting prompts to shape the model's output without altering its core structure
B.
Preventing a model from generating malicious content
Answers
B.
Preventing a model from generating malicious content
C.
Personalizing the training of a model to produce biased outputs
Answers
C.
Personalizing the training of a model to produce biased outputs
D.
Punishing the model for generating incorrect answers
Answers
D.
Punishing the model for generating incorrect answers
Suggested answer: A

Explanation:

Definition of P-Tuning: P-Tuning is a method where specific prompts are adjusted to influence the model's output. It involves optimizing prompt parameters to guide the model's responses effectively.

Functionality: Unlike traditional fine-tuning, which modifies the model's weights, P-Tuning keeps the core structure intact. This approach allows for flexible and efficient adaptation of the model to various tasks without extensive retraining.

Applications: P-Tuning is particularly useful for quickly adapting large language models to new tasks, improving performance without the computational overhead of full model retraining.

asked 16/09/2024
Vladimir Kiseliov
37 questions
User
Your answer:
0 comments
Sorted by

Leave a comment first