Question 6Which of the following are Parameter Efficient Fine-Tuning (PEFT) methods? Select all that apply.1 pointSubtractiveSelectiveAdditiveReparameterization
Question
Question 6Which of the following are Parameter Efficient Fine-Tuning (PEFT) methods? Select all that apply.1 pointSubtractiveSelectiveAdditiveReparameterization
Solution
The question is asking to identify which of the given options are considered Parameter Efficient Fine-Tuning (PEFT) methods. The options provided are:
- Subtractive
- Selective
- Additive
- Reparameterization
To answer this question, we would need to have specific knowledge about PEFT methods. However, without that information, it's impossible to provide a correct answer.
In general, PEFT methods are techniques used in machine learning to fine-tune models in a way that is efficient in terms of the number of parameters. These methods can involve various strategies, such as adding, subtracting, or modifying parameters, or reparameterizing the model in some way.
Without specific knowledge about which of these strategies are considered PEFT methods, we cannot answer the question. It would be best to refer to the specific literature or course material that the question is based on.
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