# High-dimensional vector representation

This is a Vietnamese embedding model based on sentence-transformers, supporting both English and Vietnamese, capable of mapping text to a 1024-dimensional vector space for semantic similarity calculation and retrieval tasks.

This is a sentence-transformers model fine-tuned on intfloat/multilingual-e5-small, designed to map sentences and paragraphs into a 384-dimensional dense vector space, supporting tasks such as semantic text similarity and semantic search.

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.