Jina Embeddings V2 Base
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Jina Embeddings V2 Base
Overview :
Jina Embeddings V2 Base is an English text embedding model that supports a sequence length of 8192. It is based on the Bert architecture (JinaBert) and supports the ALiBi symmetric bidirectional variant to allow for longer sequence lengths. The model was pre-trained on the C4 dataset and further trained on a collection of over 400 million sentence pairs and negative samples from Jina AI. This model is suitable for various use cases involving long documents, including long document retrieval, semantic text similarity, text re-ranking, recommendation, RAG, and LLM-based generative search. The model has 137 million parameters and is recommended for inference on a single GPU.
Target Users :
Suitable for natural language processing tasks such as text similarity calculation, text retrieval, recommendation systems, etc.
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Use Cases
Calculate the similarity between two sentences
Perform text retrieval
Build a recommendation system
Features
Supports 8192 sequence length
Suitable for processing long documents
Supports semantic text similarity calculation
Supports text re-ranking
Supports recommendation systems
Supports generative search
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