멀티태스크 대조 학습으로 혁신하는 이중 언어 텍스트 임베딩

We introduce a novel suite of state-of-the-art bilingual text embedding models that are designed to support English and another target language. These models are capable of processing lengthy text inputs with up to 8192 tokens, making them highly versatile for a range of natural language processing tasks such as text retrieval, clustering, and semantic textual similarity (STS) calculations. By focusing on bilingual models and introducing a unique multi-task learning objective, we have significantly improved the model performance on STS tasks, which outperforms the capabilities of existing multilingual models in both target language understanding and cross-lingual evaluation tasks. Moreover, our bilingual models are more efficient, requiring fewer parameters and less memory due to their smaller vocabulary needs. Furthermore, we have expanded the Massive Text Embedding Benchmark (MTEB) to include benchmarks for German and Spanish embedding models. This integration aims to stimulate further research and advancement in text embedding technologies for these languages.

Start with 1M free tokens. Top-performing, 8192 context length bilingual embeddings for your search and RAG systems.

Jina AI's new bilingual Spanish-English embedding model brings the state-of-the-art in AI to half a billion Spanish speakers.

Jina AI introduces a German/English bilingual embedding model, featuring an extensive 8,192-token length, specifically designed to support German businesses thriving in the U.S. market.

The first bilingual Chinese-English embedding model with 8192 token-length.

Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings.