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This Model2Vec model is pre-trained using Tokenlearn. It is a distilled version of the baai/bge-base-en-v1.5 Sentence Transformer. It uses static embeddings, allowing text embeddings to be computed orders of magnitude faster on both GPU and CPU. It is designed for applications where computational resources are limited or where real-time performance is critical.
This Model2Vec model is pre-trained using Tokenlearn. It is a distilled version of the baai/bge-base-en-v1.5 Sentence Transformer. It uses static embeddings, allowing text embeddings to be computed orders of magnitude faster on both GPU and CPU. It is designed for applications where computational resources are limited or where real-time performance is critical.