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) Usage with infinity: Infinity, a MIT Licensed Inference RestAPI Server. Usage with Text Embeddings Inference (TEI): CPU: GPU: Then you can send…
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