What is Intent Classification and Why Use GPT?
Intent classification (also known as intent detection, or intent recognition) is about retrieving the intent from a piece of text. This is especially useful in a discussion (i.e. chatbots and conversational AI), in order to understand what a person wants to achieve.
For example, imagine that someone says the following:
I spent some time on your documentation but I could not figure how to add a new credit card.
It is a problem because my current card is going to expire soon and I'm affraid that it will cause a service disruption.
How can I update my credit card?
Thanks in advance,
Looking forward to hearing from you,
This intent behind this email is "update credit card".
For advanced use cases, it is possible to fine-tune Dolphin (train it with your own data), which is a great way perform paraphrasing that is perfectly tailored to your industry.
Why Use Intent Classification?
In a conversation between an AI and a human, it can be very useful to understand what the person is truly looking for or asking for. Here are a couple of examples:
Triaging Customer Requests
Support teams or sales teams receive tons of customer messages. In order to address them efficiently, it is very useful to first get the intent so one can instantly decide what to do and whether it's important or not.
It's sometimes hard for a user to find what he's looking for, especially if there're a lot of products or if the products are complex. In that case, building a chatbot that detects customers' intents and points them to the right product is a very good solution.
Control whether you want to use the model on a GPU. Machine learning models run much faster on GPUs.
AI models don't always work well with non-English languages.
We do our best to add non-English models when it's possible. See for example Fine-tuned LLaMA 2 70B, Dolphin, ChatDolphin, XLM Roberta Large XNLI, Paraphrase Multilingual Mpnet Base V2, or spaCy. Unfortunately not all the models are good at handling non-English languages.
In order to solve this challenge, we developed a multilingual module that automatically translates your input into English, performs the actual NLP operation, and then translates the result back to your original language. It makes your requests a bit slower but often returns very good results.
Even for models that natively understand non-English languages, they actually sometimes work even better with the multilingual addon.
Simply select your language in the list, and from now on you can write the input text in your own language!
This multilingual add-on is a free feature.