How to use AattCNN/granite-embedding-278m-multilingual_compressed with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("AattCNN/granite-embedding-278m-multilingual_compressed")
How to use AattCNN/granite-embedding-278m-multilingual_compressed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AattCNN/granite-embedding-278m-multilingual_compressed") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]
