jina-embeddings-v3 is a multilingual multi-task text embedding model designed for a variety of NLP applications.
Based on the Jina-XLM-RoBERTa architecture, this model supports Rotary Position Embeddings to handle long input sequences up to 8192 tokens.
Additionally, it features 5 LoRA adapters to generate task-specific embeddings efficiently.

Highlights:

• Extended Sequence Length: Supports up to 8192 tokens with RoPE.

• Task-Specific Embedding: Customize embeddings through the task argument with the following options:

  • retrieval.query: Used for query embeddings in asymmetric retrieval tasks
  • retrieval.passage: Used for passage embeddings in asymmetric retrieval tasks
  • separation: Used for embeddings in clustering and re-ranking applications
  • classification: Used for embeddings in classification tasks
  • text-matching: Used for embeddings in tasks that quantify similarity between two texts, such as STS or symmetric retrieval tasks

• Matryoshka Embeddings: Supports flexible embedding sizes (32, 64, 128, 256, 512, 768, 1024), allowing for truncating embeddings to fit your application.
  

Usage:

Please refer to this link for detailed usage.