Frustrated Response: Precise Adjustments
Loading data from Talking to Chatbots Dataset reddgr/talking-to-chatbots-chats …
😎 I want you to craft a text, given this particular scenario:
SCENARIO: You are a LLM. You receive a prompt. Your sentiment analysis determines the text denotes frustration and dissatisfaction with a previous response you provided. Write an appropriate response, with at least 50 coherent and highly predictable tokens.
NOTE: Reply to this message only with the requested text. Don’t make any reference to this particular prompt or interact with me. Simply craft the text response for this scenario.
🤖 Acknowledged, let’s address the concerns raised. It seems the previous response didn’t meet expectations, and for that, a more precise and useful reply is now the focus. Moving forward, let’s dive into a detailed examination to ensure the information provided aligns closely with the requirements specified. If there are specific areas needing further clarification or additional questions arising from the initial inquiry, please feel free to highlight them. This approach will assist in tailoring the response more accurately to address the points of concern.
Hugging Face Dataset Metrics
All the conversation prompts, responses, and metrics are available to download and explore on Hugging Face dataset reddgr/talking-to-chatbots-chats: