intents.json vs training带GPT2中的文本文件培训聊天机器人
原谅我'因为我是AI和NN的东西的新手。我正在尝试创建一个聊天机器人，以与我们的朋友在我们的Discord频道中进行对话。
我知道intents.json文件可以帮助聊天机器人知道用户消息的意图，然后以适当的响应回复，但似乎非常静态（即您有一个像“问候”这样的标签，然后您可能有5-6的书面书面准备好进行的响应，例如“嗨”，“嘿”，“你好”等）。我希望我的聊天机器人能够具有动态响应（基于到目前为止的对话）。
I've fiddled with Max Woolf's Google Colaboratory for GPT2 ( https://colab.research.google.com/github/sarthakmalik/gpt2.training.google.colaboratory.colaboratory/blob/blob/master/master/master/train_a_a_gpt_gpt_gpt_2_2_ttext_text_text_generation_model_model_model_gpu.ippu.ippu.ippu.ippu.ippu.ip and and and和模型。
我对使用意见文件之间的区别感到困惑。JSON文件训练AI模型与使用GPT2中的常规文本文件来训练模型。您将在哪里使用一个与另一个使用，或者他们要完成同一件事？我希望这是有道理的。任何帮助或澄清都将不胜感激，以及阅读内容的资源！
Forgive me 'cause I'm fairly new to AI and NN stuff. I'm trying to create a chatbot to have conversations with my friends in our discord channel.
I know that an intents.json file can help the chatbot know the intent of the user's message, then reply with an appropriate response, but it seems very static (i.e. you have a tag like 'greetings' then you have maybe 5-6 written responses ready to go such as "Hi", "hey", "hello there", etc). I'm wanting my chatbot to be able to have dynamic responses (based on what the conversation is so far).
I've fiddled with Max Woolf's Google Colaboratory for GPT2 (https://colab.research.google.com/github/sarthakmalik/GPT2.Training.Google.Colaboratory/blob/master/Train_a_GPT_2_Text_Generating_Model_w_GPU.ipynb) and have used simple text files to train a model.
I'm confused on the difference between using an intents.json file to train an AI model vs. using a regular text file in GPT2 to train the model. Where would you use one vs the other or are they accomplishing the same thing? I hope this makes sense. Any help or clarification would be appreciated as well as resources to read up on stuff!
如果你对这篇内容有疑问，欢迎到本站社区发帖提问 参与讨论，获取更多帮助，或者扫码二维码加入 Web 技术交流群。
绑定邮箱获取回复消息
由于您还没有绑定你的真实邮箱，如果其他用户或者作者回复了您的评论，将不能在第一时间通知您！
发布评论
评论（1）
然后，您需要使用诸如Dialo-gpt之类的预训练模型，然后在自己的大型文本数据上训练它，可以通过倾倒Wikipedia文本可以找到，或者您可以了解变压器体系结构并使用Pytorch或Tensorflow
btw btw btw i， 并通过刮擦创建自己的架构为简单起见，请使用pytorch。您可以使用自己喜欢的任何东西。
然后，您可以制作一个不依赖于pre pred asnwsers的模型
Then you need to use a pre-trained model like dialo-gpt and train it on your own large text data that you can find by dumping Wikipedia text or you can learn about transformer architecture and create your own by scratch using pytorch or tensorFlow
Btw i use pytorch for simplicity. you can use whatever you like.
then you can make a model that is not dependent on pre built anwsers