How AI describes DistilBERT

DistilBERT is a distilled, smaller, and faster open-source version of the BERT base model, pretrained on the same corpus with an Apache-2.0 license to mirror BERT’s capabilities more efficiently. It was trained using distillation loss, masked language modeling, and cosine embedding loss to learn similar representations while enabling faster inference for downstream tasks such as sequence classification, token classification, and question answering. The model is designed for use via the Transformers library, with practical examples like fill-mask pipelines and direct loading for custom applications.