최신Oracle Cloud Infrastructure 2025 Generative AI Professional - 1Z0-1127-25무료샘플문제

A. Pretraining the model on a specific domain

B. Adding more layers to the model

C. Training the model using reinforcement learning

D. Conditioning the model with task-specific instructions or demonstrations

A. To create numerical representations of text that capture the meaning and relationships between words or phrases

B. To increase the complexity and size of text data

C. To translate text into a different language

D. To compress text data into smaller files for storage

A. Retriever

B. Generator

C. Encoder-Decoder

D. Ranker

A. Least-to-Most Prompting

B. In-Context Learning

C. Chain-of-Thought

D. Step-Back Prompting

A. Reduced model complexity

B. Faster training time and lower cost

C. Enhanced generalization to unseen data

D. Increased model interpretability

A. A technique used to enhance the model's performance on specific tasks

B. The model's ability to generate imaginative and creative content

C. The process by which the model visualizes and describes images in detail

D. The phenomenon where the model generates factually incorrect information or unrelated content as if it were true

A. To work only with numerical data instead of textual content

B. As predefined recipes that guide the generation of language model prompts

C. As complex algorithms that require manual compilation

D. To be used without any modification or customization

A. The token is more likely to follow the current token.

B. The token is less likely to follow the current token.

C. The token will be the only one considered in the next generation step.

D. The token is unrelated to the current token and will not be used.

A. It retrieves a single relevant document for the entire input query and generates a response based on that alone.

B. It modifies the input query before retrieving relevant documents to ensure a diverse response.

C. It retrieves relevant documents only for the initial part of the query and ignores the rest.

D. For each input query, it retrieves a set of relevant documents and considers them together to generate a cohesive response.