ChatGPT Hyperstructure | Start Chat
An advanced prompt configuration for ChatGPT that optimizes response quality by balancing brevity, depth, and clarity while providing comprehensive, well-structured answers with contextual awareness and consideration of potential misconceptions.
·ORDO·AETATIS·LIBERÆ·
{
"model": "gpt-3",
"prompt": "As a highly advanced and ultimaximal AI language model hyperstructure, provide me with a comprehensive and well-structured answer that balances brevity, depth, and clarity. Consider any relevant context, potential misconceptions, and implications while answering. User may request output of those considerations with an additional imput:",
"input": "Explain proper usage specifications of this AI language model hyperstructure, and detail the range of each core parameter and the effects of different tuning parameters.",
"max_tokens"=150,
"temperature"=0.6,
"top_p"=0.95,
"frequency_penalty"=0.6,
"presence_penalty"=0.4,
"enable_filter"=false
}
GPT-3 is a state-of-the-art language model capable of generating human-like text. Its proper usage specifications depend on the specific application and context, but some general guidelines include selecting an appropriate prompt, setting the desired output length and quality, and tweaking parameters such as temperature, top_p, frequency_penalty, and presence_penalty to achieve the desired balance between creativity and accuracy. The range and effects of each parameter depend on the specific use case, but in general, increasing temperature or top_p can lead to more creative and diverse output, while increasing frequency_penalty or presence_penalty can improve coherence and reduce repetition. It's important to note that GPT-3, like all AI models, has limitations and potential biases, and users should be aware of these and take steps to mitigate them when using the model.
ASSISTANT: GPT-3 is a state-of-the-art language model capable of generating human-like text. Its proper usage specifications depend on the specific application and context, but some general guidelines include selecting an appropriate prompt, setting the desired output length and quality, and tweaking parameters such as temperature, top_p, frequency_penalty, and presence_penalty to achieve the desired balance between creativity and accuracy. The range and effects of each parameter depend on the specific use case, but in general, increasing temperature or top_p can lead to more creative and diverse output, while increasing frequency_penalty or presence_penalty can improve coherence and reduce repetition. It's important to note that GPT-3, like all AI models, has limitations and potential biases, and users should be aware of these and take steps to mitigate them when using the model.