# Code Semantic Search

This is a DistilRoBERTa-based sentence transformer model specifically designed for code search tasks, capable of mapping text and code snippets into a 768-dimensional vector space.

This is a model based on sentence-transformers that can map sentences and paragraphs into a 768-dimensional dense vector space, suitable for tasks such as clustering or semantic search.

UniXcoder is a unified multimodal pretrained model that leverages multimodal data such as code comments and abstract syntax trees for pretraining code representations.

This is a sentence transformer model based on DistilRoBERTa-base, specifically designed for code search tasks, capable of mapping text and code snippets into a 768-dimensional vector space.