Free Access Oracle.1z0-1127-24.v2024-10-14.q14 Practice Test (Page 2)

Question 1

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

A.For models that require their own hosting dedicated Al duster

B.For complicated semantical undemanding improvement

C.For data sets with hundreds of thousands to millions of samples

D.For data sets with a few thousand samples or less

Question 2

Which is NOT a typical use case for LangSmith Evaluators?

A.Measuring coherence of generated text

B.Aliening code readability

C.Detecting bias or toxicity

D.Evaluating factual accuracy of outputs

Question 3

What distinguishes the Cohere Embed v3 model from its predecessor in the OCI Generative AI service?

A.Improved retrievals for Retrieval Augmented Generation (RAG) systems

B.Support for tokenizing longer sentences

C.Capacity to translate text in over u languages

D.Emphasis on syntactic clustering of word embedding's

Question 4

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.30 unit hours

C.40 unit hours

D.15 unit hours

Question 5

Which is the main characteristic of greedy decoding in the context of language model word prediction?

A.It requires a large temperature setting to ensure diverse word selection.

B.It picks the most likely word email at each step of decoding.

C.It selects words bated on a flattened distribution over the vocabulary.

D.It chooses words randomly from the set of less probable candidates.

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