Need guidance in selecting the model and the required approach
Hi, I am following the Hugging Face course. In chapter.5, the Datasets Library, at the end of the topic “Time to slice and dice”, the following exercise is given.1. Use the techniques from [Chapter 3](https://huggingface.co/course/chapter3) to train a classifier that can predict the patient condition based on the drug review.My queries:The ‘patient condition’ feature has over 1000 unique labels in the dataset. Given this fact, if I need to predict ‘patient condition’ based on ‘reviews’ feature, I think I shall first convert these two features into tensor objects. Is it correct?I see this as zero-shot classification problem. Is it correct?Further, which chekpoint/ model shall I select as the pre-trained classifier, for me to train on the dataset? How do I configure the two tensor objects in the model?Appreciate inputs.