| from typing import List | |
| from sentence_transformers import SentenceTransformer | |
| from sentence_transformers.models import StaticEmbedding | |
| from synthetic_dataset_generator.constants import STATIC_EMBEDDING_MODEL | |
| static_embedding = StaticEmbedding.from_model2vec(STATIC_EMBEDDING_MODEL) | |
| 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() | |