ClovisEmbeddings
A model that transforms text into semantic vectors (embeddings). Used for semantic search, similarity, clustering, and vector indexing in RAG pipelines.
Capabilities
InputWhat you can send
ContentText or a batch of texts
Accepted formatsTextList of texts
OutputWhat the model produces
Vector size1,024 dimensions
Output formatsFloatBase64
Batch processingYes
Billed tokensInput only