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Generative AI with LLMs: Soft Prompt: A Learned and Optimized Input for LLMs

Learn what a soft prompt is and how it can help you fine-tune large language models (LLMs) with minimal resources and maximal performance.

Question

What is a soft prompt in the context of LLMs (Large Language Models)?

A. A set of trainable tokens that are added to a prompt and whose values are updated during additional training to improve performance on specific tasks.
B. A strict and explicit input text that serves as a starting point for the model’s generation.
C. A technique to limit the creativity of the model and enforce specific output patterns.
D. A method to control the model’s behavior by adjusting the learning rate during training.

Answer

A. A set of trainable tokens that are added to a prompt and whose values are updated during additional training to improve performance on specific tasks.

Explanation

The correct answer is A. A soft prompt is a set of trainable tokens that are added to a prompt and whose values are updated during additional training to improve performance on specific tasks. A soft prompt is a type of prompt engineering technique that aims to guide a large language model (LLM) to generate desired outputs without modifying the model’s parameters. Unlike a hard prompt, which is a fixed and human-designed text input, a soft prompt is a learned and optimized input that consists of a sequence of embedding vectors. These vectors are initialized randomly and then fine-tuned along with the task-specific objective function. A soft prompt can adapt to different tasks or domains by learning the optimal values for the embedding vectors that can activate the relevant knowledge and skills of the LLM. A soft prompt can also reduce the computational and storage costs of fine-tuning, as well as the risk of overfitting or catastrophic forgetting.

Generative AI Exam Question and Answer

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Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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