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1z0-1127-24 PDF Questions and Testing Engine With 42 Questions
NEW QUESTION # 22
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.
L Calculate the total number of wheels needed for 3 cars. Cars have 4 wheels each. Then, use the total number of wheels to determine how many sets of wheels we can buy with $200 if one set (4 wheels) costs $50.
2. Solve a complex math problem by first identifying the formula needed, and then solve a simpler version of the problem before tackling the full question.
3. To understand the impact of greenhouse gases on climate change, let's start by defining what greenhouse gases are. Next, well explore how they trap heat in the Earths atmosphere.
- A. 1:Chain-of-Thought ,2:Step-Back, 3:Least-to most
- B. 1:Least-to-most, 2 Chain-of-Thought, 3:Step-Back
- C. 1:Chain-of-throught, 2: Least-to-most, 3:Step-Back
- D. 1:Step-Back, 2:Chain-of-Thought, 3:Least-to-most
Answer: D
NEW QUESTION # 23
Which is the main characteristic of greedy decoding in the context of language model word prediction?
- A. It picks the most likely word email at each step of decoding.
- B. It selects words bated on a flattened distribution over the vocabulary.
- C. It chooses words randomly from the set of less probable candidates.
- D. It requires a large temperature setting to ensure diverse word selection.
Answer: A
NEW QUESTION # 24
An AI development company is working on an advanced AI assistant capable of handling queries in a seamless manner. Their goal is to create an assistant that can analyze images provided by users and generate descriptive text, as well as take text descriptions and produce accurate visual representations. Considering the capabilities, which type of model would the company likely focus on integrating into their AI assistant?
- A. A Retrieval Augmented Generation (RAG) model that uses text as input and output
- B. A Large Language Model based agent that focuses on generating textual responses
- C. A language model that operates on a token-by-token output basis
- D. A diffusion model that specializes in producing complex outputs.
Answer: A
NEW QUESTION # 25
Given the following code: chain = prompt |11m
- A. LCEL is a programming language used to write documentation for LangChain.
- B. Which statement is true about LangChain Expression language (ICED?
- C. LCEL is a legacy method for creating chains in LangChain
- D. LCEL is a declarative and preferred way to compose chains together.
Answer: A
NEW QUESTION # 26
How does the integration of a vector database into Retrieval-Augmented Generation (RAG)-based Large Language Models(LLMS) fundamentally alter their responses?
- A. It transforms their architecture from a neural network to a traditional database system.
- B. It limits their ability to understand and generate natural language.
- C. It shifts the basis of their responses from pretrained internal knowledge to real-time data retrieval.
- D. It enables them to bypass the need for pretraining on large text corpora.
Answer: C
NEW QUESTION # 27
When should you use the T-Few fine-tuning method for training a model?
- A. For complicated semantical undemanding improvement
- B. For models that require their own hosting dedicated Al duster
- C. For data sets with hundreds of thousands to millions of samples
- D. For data sets with a few thousand samples or less
Answer: C
NEW QUESTION # 28
Which is a cost-related benefit of using vector databases with Large Language Models (LLMs)?
- A. They increase the cost due to the need for real- time updates.
- B. They require frequent manual updates, which increase operational costs.
- C. They are more expensive but provide higher quality data.
- D. They offer real-time updated knowledge bases and are cheaper than fine-tuned LLMs.
Answer: D
NEW QUESTION # 29
Which statement is true about the "Top p" parameter of the OCI Generative AI Generation models?
- A. Top p selects tokens from the "Top k' tokens sorted by probability.
- B. Top p limits token selection based on the sum of their probabilities.
- C. Top p assigns penalties to frequently occurring tokens.
- D. Top p determines the maximum number of tokens per response.
Answer: B
NEW QUESTION # 30
Which Oracle Accelerated Data Science (ADS) class can be used to deploy a Large Language Model (LLM) application to OCI Data Science model deployment?
- A. RetrievalQA
- B. Chain Deployment
- C. GenerativeAI
- D. Text Leader
Answer: C
NEW QUESTION # 31
You create a fine-tuning dedicated AI cluster to customize a foundational model with your custom training dat a. How many unit hours arc required for fine-tuning if the cluster is active for 10 hours?
- A. 10 unit hours
- B. 40 unit hours
- C. 15 unit hours
- D. 30 unit hours
Answer: A
NEW QUESTION # 32
Which role docs a "model end point" serve in the inference workflow of the OCI Generative AI service?
- A. Evaluates the performance metrics of the custom model
- B. Hosts the training data for fine-tuning custom model
- C. Serves as a designated point for user requests and model responses
- D. Updates the weights of the base model during the fine-tuning process
Answer: B
NEW QUESTION # 33
What does a higher number assigned to a token signify in the "Show Likelihoods" feature of the language model token generation?
- A. The token is unrelated to the current token and will not be used.
- B. The token is less likely to follow the current token.
- C. The token is more likely to follow the current token.
- D. The token will be the only one considered in the next generation step.
Answer: C
NEW QUESTION # 34
Which is NOT a category of pertained foundational models available in the OCI Generative AI service?
- A. Translation models
- B. Generation models
- C. Embedding models
- D. Summarization models
Answer: A
NEW QUESTION # 35
How does the utilization of T-Few transformer layers contribute to the efficiency of the fine-tuning process?
- A. By restricting updates to only a specific croup of transformer Layers
- B. By excluding transformer layers from the fine-tuning process entirely
- C. By allowing updates across all layers of the model
- D. By incorporating additional layers to the base model
Answer: A
NEW QUESTION # 36
In LangChain, which retriever search type is used to balance between relevancy and diversity?
- A. similarity
- B. similarity_score_threshold
- C. top k
- D. mmr
Answer: A
NEW QUESTION # 37
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. Continuously throughout the entire chain execution process
- B. Before user input and after chain execution
- C. After user input but before chain execution, and again after core logic but before output
- D. Only after the output has been generated
Answer: D
NEW QUESTION # 38
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