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.
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