A low dimension static embedding model (3d) to be used as a text encoder in ML pipelines
Installation
Install model2vec using pip:
pip install model2vec
from sentence_transformers import SentenceTransformer
# Load a pretrained Sentence Transformer model
model = SentenceTransformer("cnmoro/low-dimension-static-model")
# Compute text embeddings
embeddings = model.encode(["Example sentence"])
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from model2vec import StaticModel model = StaticModel.from_pretrained("cnmoro/low-dimension-static-model")