1Z0-1127-25 무료 덤프문제 온라인 액세스

How does the utilization of T-Few transformer layers contribute to the efficiency of the fine-tuning process?

• A.By allowing updates across all layers of the model
• B.By incorporating additional layers to the base model
• C.By restricting updates to only a specific group of transformer layers
• D.By excluding transformer layers from the fine-tuning process entirely

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 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.

What is the function of "Prompts" in the chatbot system?

• A.They are responsible for the underlying mechanics of the chatbot.
• B.They store the chatbot's linguistic knowledge.
• C.They are used to initiate and guide the chatbot's responses.
• D.They handle the chatbot's memory and recall abilities.

What does accuracy measure in the context of fine-tuning results for a generative model?

• A.How many predictions the model made correctly out of all the predictions in an evaluation
• B.The number of predictions a model makes, regardless of whether they are correct or incorrect
• C.The depth of the neural network layers used in the model
• D.The proportion of incorrect predictions made by the model during an evaluation

What happens if a period (.) is used as a stop sequence in text generation?

• A.The model stops generating text after it reaches the end of the current paragraph.
• B.The model ignores periods and continues generating text until it reaches the token limit.
• C.The model generates additional sentences to complete the paragraph.
• D.The model stops generating text after it reaches the end of the first sentence, even if the token limit is much higher.