Try Gemini 1.5 models, the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.Try Gemini 1.5 models, the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.
Optional[str]
The name of the downstream task the embeddings will be used for.
Valid values:
RETRIEVAL_QUERY
Specifies the given text is a query in a search/retrieval setting.
RETRIEVAL_DOCUMENT
Specifies the given text is a document from the corpus being searched.
SEMANTIC_SIMILARITY
Specifies the given text will be used for STS.
CLASSIFICATION
Specifies that the given text will be classified.
CLUSTERING
Specifies that the embeddings will be used for clustering.
QUESTION_ANSWERING
Specifies that the embeddings will be used for question answering.
FACT_VERIFICATION
Specifies that the embeddings will be used for fact verification.
CODE_RETRIEVAL_QUERY
Specifies that the embeddings will be used for code retrieval.
title
Optional[str]
Optional identifier of the text content.