# Multitask Text Embedding

A 1.5B-parameter general text embedding model based on the Qwen2 architecture, supporting both Chinese and English, focusing on sentence similarity computation and text retrieval tasks.

cde-small-v1 is a small sentence embedding model based on transformer architecture, excelling in multiple text classification, clustering, and retrieval tasks.

A 7B-parameter instruction-tuned model based on Qwen2 architecture, specializing in sentence similarity computation and text embedding tasks

A T5 architecture-based sentence embedding model focused on semantic similarity and information retrieval tasks for English text.

GTE-Large is a powerful sentence transformer model focused on sentence similarity and text embedding tasks, excelling in multiple benchmark tests.

E5-base is a general-purpose text embedding model suitable for various natural language processing tasks such as classification, retrieval, clustering, and semantic similarity calculation.