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5d2b7d1c127036ae98b9d487eca4d48744edc709.pip install -U sentence-transformers1from sentence_transformers import SentenceTransformer
2sentences = ["This is an example sentence", "Each sentence is converted"]
3
4model = SentenceTransformer('sentence-transformers/average_word_embeddings_glove.6B.300d')
5embeddings = model.encode(sentences)
6print(embeddings)SentenceTransformer(
(0): WordEmbeddings(
(emb_layer): Embedding(400001, 300)
)
(1): Pooling({'word_embedding_dimension': 300, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
)1@inproceedings{reimers-2019-sentence-bert,
2 title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
3 author = "Reimers, Nils and Gurevych, Iryna",
4 booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
5 month = "11",
6 year = "2019",
7 publisher = "Association for Computational Linguistics",
8 url = "http://arxiv.org/abs/1908.10084",
9}