# Long text embedding

A sentence transformer model fine-tuned based on Redis Langcache Embed v1, used to generate 768-dimensional sentence embedding vectors

This is a sentence-transformers model fine-tuned from Alibaba NLP/gte-modernbert-base, designed for semantic text similarity computation to implement semantic caching functionality.

Vietnamese embedding model fine-tuned on BGE-M3, enhancing Vietnamese retrieval capabilities

RoSEtta is a general-purpose Japanese text embedding model, excelling in retrieval tasks, supporting sequence lengths of up to 1024 tokens, and suitable for sentence similarity calculation and paragraph retrieval.

This is a sentence transformer model based on SlovakBERT, specifically designed for sentence similarity computation and feature extraction tasks.