This is a fine-tuned BERT4patent model that is suitable for generating embeddings for patent texts.
The resulting embeddings are suitable for a variety of downstream tasks, including classification, clustering, and retrieval.
This model leverages domain-specific training following the mirror-bert approach to further capture the language in patent documents, providing high-quality
representations for the analysis of patents.
