Model2VecEmbeddingFunction

Model2VecEmbeddingFunction is a class in pymilvus that handles encoding text into embeddings using the model2vec module to support embedding retrieval in Milvus.

Python

pymilvus.model.dense.Model2VecEmbeddingFunction

Constructor

Constructs an Model2VecEmbeddingFunction for common use cases.

Python

Model2VecEmbeddingFunction(
    model_source: Union[str, Path] = "minishlab/potion-base-8M",
    **kwargs
)

PARAMETERS:

• model_source (string) -

  The source of the model, which can either be a Hugging Face model identifier or a local path to a model2vec embedding model.

  Valid options for Hugging Face model identifier are minishlab/potion-base-8M (default), minishlab/potion-base-4M, minishlab/potion-base-2M, minishlab/potion-base-32M, and minishlab/potion-retrieval-32M

• **kwargs

  Allows additional keyword arguments to be passed to the model initialization when loading a model from the Hugging Face Hub, including parameters such as huggingface authentication tokens.

Examples

Python

from pymilvus import model

model2vec_ef = Model2VecEmbeddingFunction(
    model_source="minishlab/potion-base-8M" # Specify the model source (loads from Hugging Face or local path)
)