# High-precision semantic matching

This is a cross-encoder model fine-tuned on cross-encoder/ms-marco-MiniLM-L12-v2, designed for text reranking and semantic search.

This is a sentence-transformers model fine-tuned from Alibaba-NLP/gte-multilingual-base, supporting Vietnamese for tasks like semantic text similarity.

This is a cross-encoder model fine-tuned from ModernBERT-large, used to calculate the scores of text pairs, suitable for text re-ranking and semantic search tasks.

A 7B-parameter multilingual text embedding model developed by Alibaba NLP team, specializing in sentence similarity tasks, offering multiple quantization versions

This model is a fine-tuned sentence embedding model based on ModernBERT-base, specifically designed for sentence similarity tasks and supports English text processing.

This is a sentence transformer model based on ModernBERT-base, specifically designed for calculating sentence similarity and information retrieval tasks.

Snowflake Arctic M Long is a sentence-transformers-based sentence embedding model focused on sentence similarity and feature extraction tasks.

SPLADE-v3-DistilBERT is the DistilBERT version of naver/splade-v3, which performs excellently in tasks such as information retrieval.

A large-scale Polish sentence transformation model based on the RoBERTa architecture, focusing on sentence similarity calculation and feature extraction tasks.

A natural language inference (NLI) model based on the DeBERTa architecture, suitable for zero-shot classification tasks, converted to ONNX format for compatibility with Transformers.js

This is a sentence-transformers model based on the Greek Media BERT (uncased) model, designed to map Greek sentences and paragraphs into a 768-dimensional vector space.

This model is a fine-tuned version of paraphrase-multilingual-mpnet-base-v2, supporting English and German sentence similarity calculation, suitable for multilingual text embedding tasks.

KoSimCSE-BERT-multitask is a high-performance Korean sentence embedding model based on BERT architecture and optimized with multi-task learning strategy, specifically designed for generating high-quality Korean sentence embeddings.

French sentence embedding model based on Camembert-base for calculating sentence similarity

A cross-encoder based on RoBERTa-large for detecting duplicate questions on Quora

SGPT-5.8B is a sentence transformer model based on the weighted mean method, focusing on sentence similarity tasks, trained on the msmarco dataset and optimized with specb-bitfit technology

SGPT-2.7B is a sentence transformer model based on the weighted mean method, focusing on sentence similarity tasks, trained on the MSMARCO dataset with BitFit technology applied.