# English semantic matching

This model is a quantized version of ntproctor/mass-academy-faq-embedder, offering multiple quantization type options, suitable for efficient feature extraction and sentence similarity calculation.

Static quantized version of ColBERTv2.0, based on lightonai/colbertv2.0 model, offering multiple quantization options

This is a sentence embedding model fine-tuned from BAAI/bge-base-en-v1.5, specifically designed for financial domain texts. It can map sentences and paragraphs to a 768-dimensional vector space.

A sentence similarity calculation model based on the CompCSE dedicated dataset, suitable for English text processing.