gte-multilingual-reranker-base EU AI Act Compliance Profile

gte-multilingual-reranker-base

The gte-multilingual-reranker-base model is the first reranker model in the GTE family of models, featuring several key attributes:

• High Performance: Achieves state-of-the-art (SOTA) results in multilingual retrieval tasks and multi-task representation model evaluations when compared to reranker models of similar size.
• Training Architecture: Trained using an encoder-only transformers architecture, resulting in a smaller model size. Unlike previous models based on decode-only LLM architecture (e.g., gte-qwen2-1.5b-instruct), this model has lower hardware requirements for inference, offering a 10x increase in inference speed.
• Long Context: Supports text lengths up to 8192 tokens.
• Multilingual Capability: Supports over 70 languages.

Model Information

• Model Size: 306M
• Max Input Tokens: 8192

Usage

• It is recommended to install xformers and enable unpadding for acceleration, refer to enable-unpadding-and-xformers.
• How to use it offline: new-impl/discussions/2

Using Huggingface transformers (transformers>=4.36.0)

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