Task-oriented finetuning for better embeddings on neural search
The text embedding suit trained by [Jina AI](https://github.com/jina-ai), [Finetuner team](https://github.com/jina-ai/finetuner). ## Intented Usage & Model Info `jina-embedding-s-en-v1` is a language model that has been trained using Jina AI's Linnaeus-Clean dataset. This dataset consists of 380 million pairs of sentences, which include both query-document pairs. These pairs were obtained from various domains and were carefully selected through a thorough cleaning process. The Linnaeus-Full dataset, from which the Linnaeus-Clean dataset is derived, originally contained 1.6 billion sentence pairs. The model has a range of use cases, including information retrieval, semantic textual similarity, text reranking, and more. With a compact size of just 35 million parameters, the model enables lightning-fast inference while still delivering impressive performance. Additionally, we provide the following options: - jina-embedding-b-en-v1: 110 million parameters. - jina-embedding-l-en-v1: 800 million parameters. - jina-embedding-xl-en-v1: 3 billion parameters. - jina-embedding-xxl-en-v1: 11 billion parameters. ## Data & Parameters ## Metrics ## Usage