Introduction

We are excited to introduce the gte-modernbert series of models, which are built upon the latest modernBERT pre-trained encoder-only foundation models. The gte-modernbert series models include both text embedding models and rerank models. The gte-modernbert models demonstrates competitive performance in several text embedding and text retrieval evaluation tasks when compared to similar-scale models from the current open-source community. This includes assessments such as MTEB, LoCO, and COIR evaluation. Model Overview Developed by: Tongyi Lab, Alibaba Group Model Type: Text Embedding Primary Language: English Model Size: 149M Max Input Length: 8192 tokens Output Dimension: 768

Benchmarking

Training

Parameters