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jina-embeddings-v3 - AI Embedding Models Tool

Overview

jina-embeddings-v3 is a multilingual, multi-task text embedding model developed by Jina AI. It produces embeddings for retrieval, classification, text-matching, and other NLP tasks. Built on the Jina-XLM-RoBERTa architecture, the model employs task-specific LoRA adapters and supports rotary position embeddings for inputs up to 8192 tokens, with adjustable embedding dimensions.

Key Features

  • Multilingual, multi-task text embedding model
  • Built on Jina-XLM-RoBERTa architecture
  • Employs task-specific LoRA adapters for task adaptation
  • Supports rotary position embeddings up to 8192 tokens
  • Adjustable embedding dimensions for flexible vector sizes
  • Suitable for retrieval, classification, and text matching

Ideal Use Cases

  • Semantic search and document retrieval across languages
  • Cross-lingual text classification and labeling
  • Text matching and paraphrase detection
  • Long-context embedding when inputs approach 8192 tokens
  • Feature vectors for downstream ranking or clustering

Getting Started

  • Open the model page on Hugging Face
  • Review the model card and usage instructions
  • Download or load the model with your framework
  • Configure task-specific LoRA adapters if required
  • Set sequence length up to 8192 tokens when needed
  • Adjust embedding dimension per application needs

Pricing

Not disclosed on the Hugging Face model page; check hosting or provider for deployment costs.

Limitations

  • Pricing and licensing details are not provided on the model page
  • Task adapters may require additional configuration and resources
  • No explicit performance benchmarks were provided in the provided context

Key Information

  • Category: Embedding Models
  • Type: AI Embedding Models Tool
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