What does a dedicated RDMA cluster network do during model fine-tuning and inference?

• It limits the number of fine-tuned models deployable on the same GPU cluster.
• It leads to higher latency in model inference.
• It increases GPU memory requirements for model deployment.
• It enables the deployment of multiple fine-tuned models within a single cluster

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

• Generative Ai
• Text Loader
• Chain Deployment
• RetrievalQA

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 retrieves documents only at the beginning of the response generation and uses those for the entire content.
• RAG Token does not use document retrieval but generates responses based on pre-existing knowledge only.

• RAG Token retrieves relevant documents for each part of the response and constructs the answer incrementally.

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

• Encoder-decoder
• Generator
• Ranker
• Retriever

Which is NOT a typical use case for LangSmith Evaluators? 

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

What is the primary purpose of LangSmith Tracing? 

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

You create a fine-tuning dedicated Al cluster to customize a foundational model with your custom training. How many unit hours are required for fine-tuning if the cluster is active for 10 hours? 

• 30 unit hours
• 25 unit hours
• 20 unit hours
• 40 unit hours

How does the architecture of dedicated Al clusters contribute to minimizing GPU memory overhead for TFew fine-tuned model inference?

• By optimizing GPU memory utilization for each model's unique parameters
• By sharing base model weights across multiple fine-tuned models on the same group of GPUs

• By loading the entire model into GPU memory for efficient processing
• By allocating separate GPUs for each model instance.

Which statement is true about LangChain Expression Language (LCEL)?

• LCELis an older Python library for building Large Language Models.
• LCEL is a declarative and preferred way to compose chains together.
• LCELis a programming language used to write documentation for LangChain.
• LCELis a legacy method for creating chains in LangChain.

Given a block of code: gaConversational Retrieval Chain. from_11m (11m, retriever=rety, memory=memory) when does a chain typically interact with memory during execution? After user input but before chain execution, and again after core logic but before output Only after the output has been generated Continuously throughout the entire chain execution process Before user input and after chain execution. Given the following code: prompt Prompt Template (input_variables= ["human_input", "city"], templatetemplate) Which statement is true about Prompt Template in relation to input_variables?

• Prompt Template is unable to use any variables.
• Prompt Template requires a minimum of two variables to function properly.

• Prompt Template can support only a single variable at a time.
• Prompt Template supports any number of variables, including the possibility of having none.