How to Leverage Pre-Trained Transformer Models for Custom Text Categorisation

Zero-shot classification is a technique that allows you to classify text into categories without training a specific model for that task. Instead, it uses pre-trained models that have been trained on a large amount of data to perform this classification. The models are typically trained on a variety of tasks, including language modelling, text completion, and text entailment, among others. To perform zero-shot classification, you simply need to provide the pre-trained model with some text and a list of possible categories. The model will then use its understanding of language and its pre-existing knowledge to classify the text into one of the provided categories.