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pip install -U sentence-transformers1from sentence_transformers import SentenceTransformer
2sentences = ["This is an example sentence", "Each sentence is converted"]
3
4model = SentenceTransformer('lambdaofgod/document-readme-nbow-nbow-mnrl')
5embeddings = model.encode(sentences)
6print(embeddings)SentenceTransformer(
(0): WordEmbeddings(
(emb_layer): Embedding(53559, 200)
)
(1): WordWeights(
(emb_layer): Embedding(53559, 1)
)
(2): Pooling({'word_embedding_dimension': 200, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
)