Oracle 1Z0-1127-25 Online Practice Questions and Exam Preparation

Oracle 1Z0-1127-25 Online Questions & Answers

• Question 1:

  Why is it challenging to apply diffusion models to text generation?

  A. Because text generation does not require complex models
  B. Because text is not categorical
  C. Because text representation is categorical unlike images
  D. Because diffusion models can only produce images
  C. Because text representation is categorical unlike images

• Question 2:

  Which statement best describes the role of encoder and decoder models in natural language processing?

  A. Encoder models and decoder models both convert sequences of words into vector representations without generating new text.
  B. Encoder models take a sequence of words and predict the next word in the sequence, whereas decoder models convert a sequence of words into a numerical representation.
  C. Encoder models convert a sequence of words into a vector representation, and decoder models take this vector representation to generate a sequence of words.
  D. Encoder models are used only for numerical calculations, whereas decoder models are used to interpret the calculated numerical values back into text.
  C. Encoder models convert a sequence of words into a vector representation, and decoder models take this vector representation to generate a sequence of words.

• Question 3:

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

  A. Iteratively refining the ask to elicit a desired response
  B. Adding more layers to the neural network
  C. Adjusting the hyperparameters of the model
  D. Training the model on a large dataset
  A. Iteratively refining the ask to elicit a desired response

• Question 4:

  What differentiates Semantic search from traditional keyword search?

  A. It relies solely on matching exact keywords in the content.
  B. It depends on the number of times keywords appear in the content.
  C. It involves understanding the intent and context of the search.
  D. It is based on the date and author of the content.
  C. It involves understanding the intent and context of the search.

• Question 5:

  What does the term "hallucination" refer to in the context of Large Language Models (LLMs)?

  A. The model's ability to generate imaginative and creative content
  B. A technique used to enhance the model's performance on specific tasks
  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
  D. The phenomenon where the model generates factually incorrect information or unrelated content as if it were true

• Question 6:

  What does "Loss" measure in the evaluation of OCI Generative AI fine-tuned models?

  A. The difference between the accuracy of the model at the beginning of training and the accuracy of the deployed model
  B. The percentage of incorrect predictions made by the model compared with the total number of predictions in the evaluation
  C. The improvement in accuracy achieved by the model during training on the user- uploaded dataset
  D. The level of incorrectness in the model's predictions, with lower values indicating better performance
  D. The level of incorrectness in the model's predictions, with lower values indicating better performance

• Question 7:

  What is the purpose of embeddings in natural language processing?

  A. To increase the complexity and size of text data
  B. To translate text into a different language
  C. To create numerical representations of text that capture the meaning and relationships between words or phrases
  D. To compress text data into smaller files for storage
  C. To create numerical representations of text that capture the meaning and relationships between words or phrases

• Question 8:

  What is the purpose of memory in the LangChain framework?

  A. To retrieve user input and provide real-time output only
  B. To store various types of data and provide algorithms for summarizing past interactions
  C. To perform complex calculations unrelated to user interaction
  D. To act as a static database for storing permanent records
  B. To store various types of data and provide algorithms for summarizing past interactions

• Question 9:

  What is the purpose of Retrievers in LangChain?

  A. To train Large Language Models
  B. To retrieve relevant information from knowledge bases
  C. To break down complex tasks into smaller steps
  D. To combine multiple components into a single pipeline
  B. To retrieve relevant information from knowledge bases

• Question 10:

  How does the structure of vector databases differ from traditional relational databases?

  A. A vector database stores data in a linear or tabular format.
  B. It is not optimized for high-dimensional spaces.
  C. It is based on distances and similarities in a vector space.
  D. It uses simple row-based data storage.
  C. It is based on distances and similarities in a vector space.