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from typing import List
from sentence_transformers import SentenceTransformer
from sentence_transformers.models import StaticEmbedding
# Initialize a StaticEmbedding module
static_embedding = StaticEmbedding.from_model2vec("minishlab/M2V_base_output")
model = SentenceTransformer(modules=[static_embedding])
def get_embeddings(texts: List[str]) -> List[List[float]]:
return [embedding.tolist() for embedding in model.encode(texts)]
def get_sentence_embedding_dimensions() -> int:
return model.get_sentence_embedding_dimension()
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