Online Access Free 1Z0-1127-25 Exam Questions

What is the characteristic of T-Few fine-tuning for Large Language Models (LLMs)?

• A.It selectively updates only a fraction of weights to reduce computational load and avoid overfitting.
• B.It selectively updates only a fraction of weights to reduce the number of parameters.
• C.It updates all the weights of the model uniformly.
• D.It increases the training time as compared to Vanilla fine-tuning.

How does the temperature setting in a decoding algorithm influence the probability distribution over the vocabulary?

• A.Temperature has no effect on probability distribution; it only changes the speed of decoding.
• B.Increasing the temperature flattens the distribution, allowing for more varied word choices.
• C.Decreasing the temperature broadens the distribution, making less likely words more probable.
• D.Increasing the temperature removes the impact of the most likely word.

What does in-context learning in Large Language Models involve?

• A.Conditioning the model with task-specific instructions or demonstrations
• B.Training the model using reinforcement learning
• C.Adding more layers to the model
• D.Pretraining the model on a specific domain

What is the purpose of Retrievers in LangChain?

• A.To combine multiple components into a single pipeline
• B.To train Large Language Models
• C.To break down complex tasks into smaller steps
• D.To retrieve relevant information from knowledge bases

What is the function of the Generator in a text generation system?

• A.To collect user queries and convert them into database search terms
• B.To generate human-like text using the information retrieved and ranked, along with the user's original query
• C.To store the generated responses for future use
• D.To rank the information based on its relevance to the user's query