# Contrastive Learning Optimization

CLIP image encoder based on ConvNeXt architecture, trained by LAION, suitable for multimodal vision-language tasks

InstructCIR is an instruction-aware contrastive learning-based compositional image retrieval model, utilizing ViT-L-224 and Phi-3.5-Mini architectures, focusing on image-text-to-text generation tasks.

Nova is a generative language model for assembly code, focusing on binary code analysis tasks

A text embedding model fine-tuned based on BAAI/bge-large-en-v1.5, trained using the MEDI dataset and mined triplets from the MTEB classification task training set, capable of encoding retrieval queries directly without instructions.

BioLORD-2023-C is a sentence transformer model trained based on BioLORD, focusing on generating meaningful representations for biomedical and clinical texts.

Nova is a generative language model for assembly code, focusing on binary code analysis tasks

A coin image retrieval model fine-tuned based on CLIP, enhancing feature extraction capabilities for coin images

A lightweight sentence embedding model optimized based on the MiniLM architecture, specifically designed for efficient sentence similarity calculation

Sentence embedding model trained on the French legal information retrieval dataset LLeQA, suitable for semantic search and clustering tasks in legal texts

A French sentence embedding model based on CamemBERT, specifically optimized for French legal information retrieval tasks, capable of converting text into 768-dimensional vector space representations.

Biomedical sentence embedding model based on BioLinkBERT, specifically designed for biomedical text similarity calculation

BioLORD is a novel pre-training strategy model designed to generate semantic representations for clinical statements and biomedical concepts

A sentence embedding model fine-tuned from MiniLM-L6-H384-uncased pre-trained model, specifically designed for semantic similarity calculation in Q&A scenarios

Sentence embedding model fine-tuned on 700 million Reddit dialogue sentence pairs using contrastive learning, based on the MPNet-base pre-trained model

A DistilBERT-based sentence embedding model optimized for question-answer similarity tasks, trained using contrastive learning

A sentence embedding model based on DistilBERT, optimized for question-answer similarity tasks, fine-tuned on various QA datasets through contrastive learning