A developer is preparing a data sample to train a language model to act as a helpful, concise code reviewer. The complete input for the model is constructed by combining several pieces of text. Match each component name on the left with its corresponding text from the input sample on the right.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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System Information in LLM Inputs
A developer is preparing a data sample to train a language model to act as a helpful, concise code reviewer. The complete input for the model is constructed by combining several pieces of text. Match each component name on the left with its corresponding text from the input sample on the right.
Diagnosing Fine-Tuning Input Flaws
A developer is creating a data sample to fine-tune a language model. The complete input for the model is shown below. Analyze the text and identify the part that constitutes the 'system information', which sets the overall behavior and constraints for the model.
Input Text: "You are a helpful travel agent. Your goal is to find the most affordable travel options in Europe. Do not suggest any destination outside of Europe. Based on the user's request, provide a 3-day itinerary. User request: I want to visit Italy for 3 days on a budget of $500."