# Cross-language Search

IBM Granite multilingual embedding model, supporting text embedding tasks in 12 languages, suitable for information retrieval and multilingual application scenarios.

ColBERT-XM is a multilingual passage retrieval model based on the ColBERT architecture, supporting sentence similarity calculation and passage retrieval tasks in multiple languages.

This is a multilingual sentence embedding model based on sentence-transformers, capable of mapping text to a 1024-dimensional vector space, suitable for semantic search and clustering tasks.

CrisisTransformers is a series of pre-trained language models and sentence encoders for crisis-related social media texts, based on the RoBERTa architecture, trained on a 15-billion-token crisis event dataset.