text-generation
: Designed to produce coherent and contextually relevant natural language based on user input. Common use cases for text-generation
models are:
sentence-similarity
: Encodes text into a vector database (embedding) that captures semantic meaning. These embeddings enable efficient comparison and analysis of text based on contextual relationships. Common use cases for sentence-similarity
models are: