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)
)