# Short Text Matching

This is a fine-tuned cross-encoder model based on cross-encoder/ms-marco-MiniLM-L6-v2, primarily used for text re-ranking and semantic search tasks.

This is a fine-tuned BERT-based sentence transformer model for mapping sentences and paragraphs into a 768-dimensional vector space, supporting tasks such as semantic text similarity and semantic search.

BERT-based Arabic sentence embedding model supporting semantic text similarity tasks

A cross-encoder model trained on the TinyBERT-L4 architecture for predicting semantic similarity scores (0-1) between two sentences.