The embedding model trained by Jina AI . Jina Embeddings v4: Universal Embeddings for Multimodal Multilingual Retrieval GGUF Blog Technical Report API Intended Usage & Model Info jina embeddings v4 is a universal embedding model for multimodal and multilingual retrieval. The model is specially designed for complex document retrieval, including visually rich documents with charts, tables, and illustrations. Built on Qwen/Qwen2.5 VL 3B Instruct, jina embeddings v4 features: Unified embeddings for text, images, and visual documents, supporting both dense (single vector) and late interaction (multi vector) retrieval. Multilingual support (30+ languages) and compatibility with a wide range of domains, including technical and visually complex documents. Task specific adapters for retrieval, text matching, and code related tasks, which can be selected at inference time. Flexible embedding size : dense embeddings are 2048 dimensions by default but can be truncated to as low as 128 with minimal performance loss. Summary of features: Feature Jina Embeddings V4 Base Model Qwen2.5 VL 3B Instruct Supported Tasks retrieval , text matching , code Model DType BFloat 16 Max Sequence Length 32768 Si…
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