Trained by Jina AI . jina reranker v1 tiny en This model is designed for blazing fast reranking while maintaining competitive performance . What's more, it leverages the power of our JinaBERT model as its foundation. JinaBERT itself is a unique variant of the BERT architecture that supports the symmetric bidirectional variant of ALiBi. This allows jina reranker v1 tiny en to process significantly longer sequences of text compared to other reranking models, up to an impressive 8,192 tokens. To achieve the remarkable speed, the jina reranker v1 tiny en employ a technique called knowledge distillation. Here, a complex, but slower, model (like our original jina reranker v1 base en) acts as a teacher, condensing its knowledge into a smaller, faster student model. This student retains most of the teacher's knowledge, allowing it to deliver similar accuracy in a fraction of the time. Here's a breakdown of the reranker models we provide: Model Name Layers Hidden Size Parameters (Millions) jina reranker v1 base en 12 768 137.0 jina reranker v1 turbo en 6 384 37.8 jina reranker v1 tiny en 4 384 33.0 Currently, the jina reranker v1 base en model is not available on Hugging Face. You can acces…
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