![]() Just add the files you want to edit to the list, enter the new information, and then click the save button. I found a model on HuggingFace which has been pre-trained with customer dialogues, and have read the research paper, so I was considering fine-tuning this as a starting point, but I only have experience with text (multiclass/multilabel) classification when it comes to transformers. This tag editor is designed to be easy and intuitive to use. What resources are available to research how to implement this in Python (using tensorflow or pytorch).I considered analysing each sentence and performing binary classification, but I'd like to explore options that take into account the context of the rest of the conversation if possible. The sentence either is or isn't the customers problem. I thought this might be called "intent recognition", but most guides seem to refer to multiclass classification. ![]()
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