How does the temperature setting in a decoding algorithm influence the probability distribution over the vocabulary?
Which is a characteristic of T-Few fine-tuning for Large Language Models (LLMs)?
Which technique involves prompting the Large Language Model (LLM) to emit intermediate reasoning steps as part of its response?
Which statement describes the difference between "Top k" and "Top p" in selecting the next token in the OCI Generative AI Generation models?
What does "k-shot prompting" refer to when using Large Language Models for task-specific applications?
Given the following code:
PromptTemplate(input_variables=["human_input", "city"], template=template)
Which statement is true about PromptTemplate in relation to input_variables?
Given the following prompts used with a Large Language Model, classify each as employing the Chain-of-Thought, Least-to-Most, or Step-Back prompting technique:
What distinguishes the Cohere Embed v3 model from its predecessor in the OCI Generative AI service?