최신 1z0-1127-24 무료덤프 - Oracle Cloud Infrastructure 2024 Generative AI Professional

A. PEFT involves only a few or new parameters and uses labeled, task-specific data.

B. PEFT modifies all parameters and uses unlabeled, task-agnostic data.

C. PEFT does not modify any parameters but uses soft prompting with unlabeled data. PEFT modifies

D. PEFT parameters and b typically used when no training data exists.

A. Assigns a penalty to tokens that have already appeared in the preceding text

B. Controls the randomness of the model's output, affecting its creativity

C. Determines the maximum number of tokens the model can generate per response

D. Specifies a string that tells the model to stop generating more content

A. Loss measures the total number of predictions made by a model.

B. Loss indicates how good a prediction is, and it should increase as the model improves.

C. Loss is a measure that indicates how wrong the model's predictions are.

D. Loss describes the accuracy of the right predictions rather than the incorrect ones.

A. It transforms their architecture from a neural network to a traditional database system.

B. It shifts the basis of their responses from pretrained internal knowledge to real-time data retrieval.

C. It limits their ability to understand and generate natural language.

D. It enables them to bypass the need for pretraining on large text corpora.

A. Support for tokenizing longer sentences

B. Capacity to translate text in over u languages

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

D. Emphasis on syntactic clustering of word embedding's

A. 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.

B. Encoder models and decoder models both convert sequence* of words into vector representations without generating new text.

C. Encoder models convert a sequence of words into a vector representation, and decoder models take this vector representation to 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.

A. It penalizes all tokens equally, regardless of how often they have appeared.

B. It penalizes a token each time it appears after the first occurrence.

C. It penalizes only tokens that have never appeared in the text before.

D. It applies a penalty only if the token has appeared more than twice.