# Chinese Semantic Matching

PromCSE is a supervised learning-based sentence embedding model specifically designed for calculating Chinese sentence similarity.

A Chinese semantic matching model based on the CoSENT algorithm, capable of mapping sentences into a 1024-dimensional dense vector space, suitable for tasks such as sentence embedding, text matching, or semantic search.

A BERT model based on bert-base-chinese, trained on the million-level semantic similarity dataset SimCLUE, designed for general semantic matching scenarios, demonstrating excellent generalization ability.

A BERT model based on bert-base-chinese, trained on the million-level semantic similarity dataset SimCLUE, designed for general semantic matching scenarios, demonstrating stronger generalization capabilities.