How ChatGPT Gives Correct Answers Based on Prompts Prompt Engineering For ChatGPT | Lecture 31/34

👉 Complete Playlist of Prompt Engineering For ChatGPT /playlist/PLfQLfkzgFi7aAYsKJk8RAo6acafR9uvEM Prompt engineering for ChatGPT involves designing effective prompts to elicit the desired responses from the language model. It aims to guide the model towards generating coherent and accurate answers by providing clear instructions or context. Here are some key considerations for prompt engineering: 1. Specify the format: Clearly define the format you want the response in. For example, if you expect a bullet-point list or a paragraph, explicitly mention it in the prompt. 2. Provide context: Give relevant information to set the context for the model. This can include background details, previous conversation history, or any specific constraints or requirements. 3. Ask for specific information: Be precise in your questions or requests. If you need a particular answer or specific details, make sure to explicitly ask for them in the prompt. 4. Use system messages: Use system messages to guide the behavior of the model. These messages can provide high-level instructions, encourage a certain tone or style, or remind the model about the desired output format. 5. Experiment and iterate: Prompt engineering often requires experimentation and iteration. Test different prompts, tweak instructions, and observe the model's responses to fine-tune the desired output. 6. Avoid open-ended prompts: ChatGPT tends to generate creative but sometimes unreliable responses. To mitigate this, provide narrower prompts or specify a desired approach to encourage more focused and accurate answers. 7. Combine prompts with user instructions: Include user instructions within the conversation alongside the prompts. This helps guide the model's behavior and ensure it understands and follows user requests. Remember that prompt engineering is an iterative process. Continuously refine and improve your prompts based on the model's responses and feedback from interactions. Experimentation and fine-tuning are essential for achieving the desired results with ChatGPT. Subscribe to our channel for more computer science related tutorials| /@ learnwithgeeks

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