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  The easiest way to starting using `jina-embeddings-v3` is to use Jina AI's [Embedding API](https://jina.ai/embeddings/).
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- ## Intended Usage & Model info
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  `jina-embeddings-v3` is a **multilingual multi-task text embedding model** designed for a variety of NLP applications.
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- Based on the [XLM-RoBERTa architecture](https://huggingface.co/jinaai/xlm-roberta-flash-implementation), this model supports [Rotary Position Embeddings (RoPE)](https://arxiv.org/abs/2104.09864) to handle long sequences up to **8192 tokens**.
 
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  Additionally, it features [LoRA](https://arxiv.org/abs/2106.09685) adapters to generate task-specific embeddings efficiently.
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  ### Key Features:
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  ### Model Lineage:
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  `jina-embeddings-v3` builds upon the [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) model, which was originally trained on 100 languages.
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- We extended its capabilities with an extra pretraining phase on the [CulturaX](https://huggingface.co/datasets/uonlp/CulturaX) dataset, then contrastively fine-tuned it on 30 languages for enhanced performance in both monolingual and cross-lingual setups.
 
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  ### Supported Languages:
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  While the base model supports 100 languages, we've focused our tuning efforts on the following 30 languages to maximize performance:
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- **Arabic, Bengali, Chinese, Danish, Dutch, English, Finnish, French, Georgian, German, Greek, Hindi, Indonesian, Italian, Japanese, Korean, Latvian, Norwegian, Polish, Portuguese, Romanian, Russian, Slovak, Spanish, Swedish, Thai, Turkish, Ukrainian, Urdu,** and **Vietnamese.**
 
 
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  ## Data & Parameters
 
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  The easiest way to starting using `jina-embeddings-v3` is to use Jina AI's [Embedding API](https://jina.ai/embeddings/).
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+ ## Intended Usage & Model Info
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  `jina-embeddings-v3` is a **multilingual multi-task text embedding model** designed for a variety of NLP applications.
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+ Based on the [XLM-RoBERTa architecture](https://huggingface.co/jinaai/xlm-roberta-flash-implementation),
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+ this model supports [Rotary Position Embeddings (RoPE)](https://arxiv.org/abs/2104.09864) to handle long sequences up to **8192 tokens**.
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  Additionally, it features [LoRA](https://arxiv.org/abs/2106.09685) adapters to generate task-specific embeddings efficiently.
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  ### Key Features:
 
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  ### Model Lineage:
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  `jina-embeddings-v3` builds upon the [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) model, which was originally trained on 100 languages.
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+ We extended its capabilities with an extra pretraining phase on the [CulturaX](https://huggingface.co/datasets/uonlp/CulturaX) dataset,
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+ then contrastively fine-tuned it on 30 languages for enhanced performance in both monolingual and cross-lingual setups.
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  ### Supported Languages:
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  While the base model supports 100 languages, we've focused our tuning efforts on the following 30 languages to maximize performance:
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+ **Arabic, Bengali, Chinese, Danish, Dutch, English, Finnish, French, Georgian, German, Greek,
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+ Hindi, Indonesian, Italian, Japanese, Korean, Latvian, Norwegian, Polish, Portuguese, Romanian,
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+ Russian, Slovak, Spanish, Swedish, Thai, Turkish, Ukrainian, Urdu,** and **Vietnamese.**
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  ## Data & Parameters