# English sentence embedding

A quantized version based on Alibaba NLP/gte-Qwen2-1.5B-instruct, primarily used for sentence similarity computation and text embedding tasks.

A 7B-parameter multilingual text embedding model developed by Alibaba NLP team, specializing in sentence similarity tasks, offering multiple quantization versions

all-MiniLM-L6-v2 is a lightweight sentence embedding model based on the MiniLM architecture, suitable for English text feature extraction and sentence similarity calculation.

BGE Base English v1.5 is a transformer-based sentence embedding model, specifically designed for extracting sentence features and calculating sentence similarity.

CompCSE and SimCSE are contrastive learning-based sentence embedding models for calculating sentence similarity.

A vectorizer developed by Sinequa that generates embedding vectors from input paragraphs or queries for sentence similarity computation and retrieval tasks.