Model2VecEmbeddingFunction

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

pymilvus.model.dense.Model2VecEmbeddingFunction

Constructor

Constructs an Model2VecEmbeddingFunction for common use cases.

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

from pymilvus import model

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