# Supervised Contrastive Learning

PromCSE is a supervised learning-based sentence embedding model specifically designed for calculating Chinese sentence similarity.

SimCSE (Supervised Version) is a Chinese sentence similarity calculation model based on supervised learning, optimizing sentence embeddings through contrastive learning.

A sentence transformer model initialized from sentence-transformers/all-mpnet-base-v2, specifically designed for few-shot context example retrieval in the MultiWOZ dataset

This is a CIFAR-10 image classification model trained using supervised contrastive learning techniques, achieving a test accuracy of 81.06%