jina-embeddings-v3 - AI Embedding Models Tool

Overview

jina-embeddings-v3 is a multilingual, multi-task text embedding model built on the Jina-XLM-RoBERTa architecture. It uses task-specific LoRA adapters and supports rotary position embeddings for sequences up to 8,192 tokens, with flexible embedding dimension settings for retrieval, classification, and text-matching tasks.

Key Features

• Multilingual, multi-task text embedding model
• Built on the Jina-XLM-RoBERTa architecture
• Task-specific LoRA adapters for adaptation
• Supports rotary position embeddings up to 8,192 tokens
• Flexible, adjustable embedding dimensions
• Designed for retrieval, classification, and text matching

Ideal Use Cases

• Semantic search and document retrieval
• Multilingual text classification
• Text-to-text matching and similarity scoring
• Embedding long-form documents up to 8,192 tokens
• Feature vectors for downstream ML models

Getting Started

• Open the model page on Hugging Face for jina-embeddings-v3
• Choose an embedding dimension and model variant if available
• Install Jina AI or Hugging Face integration
• Configure and attach LoRA adapters for task-specific performance
• Encode text inputs and use embeddings in downstream tasks

Pricing

Pricing information is not disclosed in the provided source.

Limitations

• Not intended for text generation; focused on embedding tasks
• Pricing and tag metadata are not provided in the source

Key Information

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