New ask Hacker News story: Prompt Engineering Made Easy
Prompt Engineering Made Easy
3 by MikahDang | 2 comments on Hacker News.
Hey HN, We've been hard at work on a tool that we believe will change the game for developers, data scientists, and anyone working with models that rely on textual prompts. I'm excited to introduce our new tool: Automated Prompt Engineering (APE). Problem: As many of you know, how you phrase a prompt can significantly impact the results you get from models, especially with sophisticated language models. It often requires numerous iterations to hone in on the right prompt to obtain the desired response. Solution: APE is designed to tackle this exact problem. With APE, you can: - Iterative Testing: Input your desired outcome, and APE will iteratively rephrase and test multiple prompts to achieve that outcome. - Optimization: APE can integrate with popular models and optimize prompts based on the model's feedback, ensuring the highest quality responses. Features: Customization: Tailor the tool according to your domain-specific requirements. Model Integration: Seamless integration with popular NLP models and platforms. Try it out: We've opened a limited beta for HN users. Get early access and let us know your feedback. Your insights will be invaluable in shaping the next iterations of APE. Link to the beta: https://ift.tt/tSdQW35
3 by MikahDang | 2 comments on Hacker News.
Hey HN, We've been hard at work on a tool that we believe will change the game for developers, data scientists, and anyone working with models that rely on textual prompts. I'm excited to introduce our new tool: Automated Prompt Engineering (APE). Problem: As many of you know, how you phrase a prompt can significantly impact the results you get from models, especially with sophisticated language models. It often requires numerous iterations to hone in on the right prompt to obtain the desired response. Solution: APE is designed to tackle this exact problem. With APE, you can: - Iterative Testing: Input your desired outcome, and APE will iteratively rephrase and test multiple prompts to achieve that outcome. - Optimization: APE can integrate with popular models and optimize prompts based on the model's feedback, ensuring the highest quality responses. Features: Customization: Tailor the tool according to your domain-specific requirements. Model Integration: Seamless integration with popular NLP models and platforms. Try it out: We've opened a limited beta for HN users. Get early access and let us know your feedback. Your insights will be invaluable in shaping the next iterations of APE. Link to the beta: https://ift.tt/tSdQW35
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