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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('avsolatorio/MixEmbedFinetune-base-20240122103720-latest')
5embeddings = model.encode(sentences)
6print(embeddings)EncoderSentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
(2): Normalize()
)