Oracle 1z0-1127-24 問題集

質問 1：
Given a block of code:
qa = Conversational Retrieval Chain, from 11m (11m, retriever-retv, memory-memory) when does a chain typically interact with memory during execution?
A. Before user input and after chain execution
B. Only after the output has been generated
C. After user input but before chain execution, and again after core logic but before output
D. Continuously throughout the entire chain execution process
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 2：
Which component of Retrieval-Augmented Generation (RAG) evaluates and prioritizes the information retrieved by the retrieval system?
A. Generator
B. Retriever
C. Encoder-decoder
D. Ranker
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 3：
Why is it challenging to apply diffusion models to text generation?
A. Because text representation is categorical unlike images
B. Because text generation does not require complex models
C. Because text is not categorical
D. Because diffusion models can only produce images
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 4：
How does the integration of a vector database into Retrieval-Augmented Generation (RAG)-based Large Language Models(LLMS) fundamentally alter their responses?
A. It limits their ability to understand and generate natural language.
B. It enables them to bypass the need for pretraining on large text corpora.
C. It shifts the basis of their responses from pretrained internal knowledge to real-time data retrieval.
D. It transforms their architecture from a neural network to a traditional database system.
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 5：
How does the architecture of dedicated Al clusters contribute to minimizing GPU memory overhead forT- Few fine-tuned model inference?
A. By optimizing GPIJ memory utilization for each model's unique para
B. By allocating separate GPUS for each model instance
C. By loading the entire model into G PU memory for efficient processing
D. By sharing base model weights across multiple fine-tuned model's on the same group of GPUs
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 6：
What is the purpose of Retrievers in LangChain?
A. To train Large Language Models
B. To combine multiple components into a single pipeline
C. To retrieve relevant information from knowledge bases
D. To break down complex tasks into smaller steps
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 7：
Which is a key characteristic of the annotation process used in T-Few fine-tuning?
A. T-Few fine-tuning requires manual annotation of input-output pain.
B. T-Few fine-tuning uses annotated data to adjust a fraction of model weights.
C. T- Few fine-tuning involves updating the weights of all layers in the model.
D. T-Few fine-tuning relies on unsupervised learning techniques for annotation.
正解：B
解説: (Topexam メンバーにのみ表示されます)