# English Semantic Understanding

This is a cross-encoder model fine-tuned from ModernBERT-base for text re-ranking and semantic search tasks.

BGE Large English v1.5 is a high-performance sentence transformer model, focusing on sentence feature extraction and similarity computation.

This dataset is used for training and evaluating the SimCSE (Simple Contrastive Learning of Sentence Embeddings) model, supporting sentence similarity tasks.

INSTRUCTOR is a text embedding model based on the T5 architecture, focusing on sentence similarity calculation and information retrieval tasks. It excels in various NLP tasks, including text classification, clustering, and semantic similarity evaluation.

This is a sentence embedding model based on the MiniLM architecture, capable of mapping text to a 384-dimensional vector space, suitable for tasks such as semantic search and sentence similarity calculation.

A model based on sentence-transformers that maps sentences and paragraphs to a 128-dimensional vector space, suitable for semantic search and clustering tasks

This is a sentence embedding model based on DistilBERT, capable of mapping sentences and paragraphs into a 32-dimensional dense vector space, suitable for tasks such as sentence similarity calculation, semantic search, and clustering.

This is a sentence embedding model based on the MPNet architecture, capable of mapping sentences and paragraphs into a 768-dimensional dense vector space, suitable for tasks like semantic search and clustering.

This is a sentence transformer model based on DistilBERT, capable of mapping sentences and paragraphs into a 768-dimensional dense vector space, suitable for sentence similarity and feature extraction tasks.

Sentence embedding model based on MPNet architecture, mapping text to a 768-dimensional vector space, suitable for semantic search and sentence similarity calculation

This model is based on the DistilBERT architecture, fine-tuned on the SQuAD2 and MIT Restaurant datasets, supporting both question answering and named entity recognition tasks.

A fine-tuned model based on DistilBERT for text classification tasks, excelling on the COLA dataset.