Free Oracle Cloud Infrastructure 2024 Generative AI Professional Exam 1Z0-1127-24 Exam Practice Test

What does "Loss" measure in the evaluation of OCI Generative AI fine-tuned models?The difference between the accuracy of the model at the beginning of training and the accuracy of the deployed model

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

When should you use the T-Few fine-tuning method for training a model?

• For complicated semantical undemanding improvement
• For models that require their own hosting dedicated Al duster
• For data sets with a few thousand samples or less
• For data sets with hundreds of thousands to millions of samples

Which is NOT a typical use case for LangSmith Evaluators?

• Measuring coherence of generated text
• Aliening code readability
• Evaluating factual accuracy of outputs
• Detecting bias or toxicity

In LangChain, which retriever search type is used to balance between relevancy and diversity?

• top k
• mmr
• similarity_score_threshold
• similarity

How does the Retrieval-Augmented Generation (RAG) Token technique differ from RAG Sequence when generating a model's response?

• Unlike RAG Sequence, RAG Token generates the entire response at once without considering individual parts.
• RAG Token does not use document retrieval but generates responses based on pre-existing knowledge only.
• RAG Token retrieves documents oar/at the beginning of the response generation and uses those for the entire content
• RAG Token retrieves relevant documents for each part of the response and constructs the answ.er incrementally.

Which Oracle Accelerated Data Science (ADS) class can be used to deploy a Large Language Model (LLM) application to OCI Data Science model deployment?

• RetrievalQA
• Text Leader
• Chain Deployment
• GenerativeAI

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?

• PromptTemplate requires a minimum of two variables to function property.
• PromptTemplate can support only a single variable M a time.
• PromptTemplate supports Any number of variable*, including the possibility of having none.
• PromptTemplate is unable to use any variables.

Which component of Retrieval-Augmented Generation (RAG) evaluates and prioritizes the information retrieved by the retrieval system?

• Retriever
• Encoder-decoder
• Ranker
• Generator

Which is a distinguishing feature of "Parameter-Efficient Fine-tuning (PEFT)" as opposed to classic Tine- tuning" in Large Language Model training?

• PEFT involves only a few or new parameters and uses labeled, task-specific data.
• PEFT modifies all parameters and uses unlabeled, task-agnostic data.
• PEFT does not modify any parameters but uses soft prompting with unlabeled data. PEFT modifies
• PEFT parameters and b typically used when no training data exists.

What is the primary purpose of LangSmith Tracing?

• To monitor the performance of language models
• To generate test cases for language models
• To analyze the reasoning process of language
• To debug issues in language model outputs