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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('embaas/sentence-transformers-e5-large-v2')
5embeddings = model.encode(sentences)
6print(embeddings)1import requests
2
3url = "https://api.embaas.io/v1/embeddings/"
4
5headers = {
6 "Content-Type": "application/json",
7 "Authorization": "Bearer ${YOUR_API_KEY}"
8}
9
10data = {
11 "texts": ["This is an example sentence.", "Here is another sentence."],
12 "instruction": "query"
13 "model": "e5-large-v2"
14}
15
16response = requests.post(url, json=data, headers=headers)SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel
(1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False})
(2): Normalize()
)