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NEW QUESTION # 35
Given the following code:
Prompt Template
(input_variable[''rhuman_input",'city''], template-template)
Which statement is true about Promt Template in relation to input_variables?
Answer: D
Explanation:
The PromptTemplate in relation to input_variables is designed to be flexible and can support any number of variables, including the possibility of having none. This means that users can define a template with multiple variables or none at all, depending on their specific needs. The PromptTemplate facilitates dynamic prompt creation by inserting variable values into predefined template slots.
Reference
LangChain documentation on PromptTemplate
Examples and tutorials on using PromptTemplate in generative AI applications
NEW QUESTION # 36
In LangChain, which retriever search type is used to balance between relevancy and diversity?
Answer: A
NEW QUESTION # 37
How does the architecture of dedicated Al clusters contribute to minimizing GPU memory overhead forT- Few fine-tuned model inference?
Answer: A
Explanation:
The architecture of dedicated AI clusters contributes to minimizing GPU memory overhead for fine-tuned model inference by sharing base model weights across multiple fine-tuned models on the same group of GPUs. This approach allows different fine-tuned models to leverage the shared base model weights, reducing the memory requirements and enabling efficient use of GPU resources. By not duplicating the base model weights for each fine-tuned model, the system can handle more models simultaneously with lower memory overhead.
Reference
Technical documentation on AI cluster architectures
Research articles on optimizing GPU memory utilization in model inference
NEW QUESTION # 38
What is the primary purpose of LangSmith Tracing?
Answer: B
NEW QUESTION # 39
What does "k-shot prompting* refer to when using Large Language Models for task-specific applications?
Answer: D
NEW QUESTION # 40
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