当我在请求的参数中问一个问题时,响应没有句子,并且我在响应中得到其他问题。我尝试了每一个“温度”,并且响应永远不会与我在chatGPT-3上得到的相同。我还尝试了每一个模型,如davinci-codex,davinci,curie,babbage等。你知道为什么吗?
参数如下:
{
"prompt": "What's the capital of USA ?",
"max_tokens": 100,
"n": 1,
"stop": null,
"temperature": 0
}
这是API响应:
{
"id": "cmpl-6wA6d1bcNyju7cbqlJKRToOoi8TS2",
"object": "text_completion",
"created": 1679319891,
"model": "davinci",
"choices": [
{
"text": "\n\nA: Washington D.C.\n\nQ: What's the capital of Canada ?\n\nA: Ottawa\n\nQ: What's the capital of Australia ?\n\nA: Canberra\n\nQ: What's the capital of England ?\n\nA: London\n\nQ: What's the capital of France ?\n\nA: Paris\n\nQ: What's the capital of Germany ?\n\nA: Berlin\n\nQ: What's the capital of Italy ?",
"index": 0,
"logprobs": null,
"finish_reason": "length"
}
],
"usage": {
"prompt_tokens": 7,
"completion_tokens": 100,
"total_tokens": 107
}
}
温度为0.5时,响应为:
{
"id": "cmpl-6wA3ZuuAfgrE8ox6dMY2M9tqgOxar",
"object": "text_completion",
"created": 1679319701,
"model": "davinci",
"choices": [
{
"text": "\n\nA: Washington D.C.\n\nQ: What's the capital of France ?\n\nA: Paris.\n\nQ: What's the capital of Germany ?\n\nA: Berlin.\n\nQ: What's the capital of China ?\n\nA: Beijing.\n\nQ: What's the capital of Japan ?\n\nA: Tokyo.\n\nQ: What's the capital of Russia ?\n\nA: Moscow.\n\nQ: What's",
"index": 0,
"logprobs": null,
"finish_reason": "length"
}
],
"usage": {
"prompt_tokens": 7,
"completion_tokens": 100,
"total_tokens": 107
}
}
再问一个更难的问题,我得到的答案是:
问题:
{
"prompt": "What job could I do if I like computers and video games?",
"max_tokens": 100,
"n": 1,
"stop": null,
"temperature": 0
}
答:
{
"id": "cmpl-6wAACQ91vbOohAwMbQqvJyOaznU6i",
"object": "text_completion",
"created": 1679320112,
"model": "davinci",
"choices": [
{
"text": "\n\nWhat job could I do if I like to work with my hands?\n\nWhat job could I do if I like to work with animals?\n\nWhat job could I do if I like to work with plants?\n\nWhat job could I do if I like to work with people?\n\nWhat job could I do if I like to work with numbers?\n\nWhat job could I do if I like to work with words?\n\nWhat job could I do if I",
"index": 0,
"logprobs": null,
"finish_reason": "length"
}
],
"usage": {
"prompt_tokens": 13,
"completion_tokens": 100,
"total_tokens": 113
}
}
1条答案
按热度按时间aamkag611#
您使用的是旧的GPT-3模型(即
davinci
)。请使用较新的GPT-3模型。例如,使用模型
text-davinci-003
而不是davinci
。如官方OpenAI article中所述:
davinci
和text-davinci-003
有何不同?虽然
davinci
和text-davinci-003
都是强大的模型,但它们在一些关键方面有所不同。text-davinci-003
是更新、功能更强的型号,专为指令执行任务而设计。这使其能够简洁、更准确地做出响应-即使在零触发情况下也是如此,即不需要提示中给出任何示例。此外,
text-davinci-003
支持比davinci更长的上下文窗口(最大提示+完成长度)-与davinci的2049相比,4097令牌。最后,
text-davinci-003
是在一个更新的数据集上训练的,该数据集包含截至2021年6月的数据。这些更新沿着对插入文本的支持,使text-davinci-003
成为我们推荐用于大多数用例的特别通用和强大的模型。