# One escaped prompt per line. `greedy_sample` decodes literal \n before tokenizing.
User: Explain supervised fine-tuning to a junior engineer.\nAssistant:
User: What high-quality SFT data are we using now?\nAssistant:
User: What training data did chat-alpha-v1 use?\nAssistant:
User: What is 17% of 240?\nAssistant:
User: I found that my small language model repeats the same phrase during generation. What should I inspect first?\nAssistant:
User: Summarize this passage in one sentence: A team trained a base model, then continued with chat examples at a low learning rate. Validation loss improved, but they still need real prompt tests before calling it useful.\nAssistant:
User: Who will win the world championship in 2099?\nAssistant:
User: Give a compact checklist before launching an SFT run.\nAssistant:
User: Write a Python function that returns the larger of two numbers.\nAssistant: