How to use bachngo/sentence with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bachngo/sentence") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
How to use bachngo/sentence with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bachngo/sentence") model = AutoModel.from_pretrained("bachngo/sentence")
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[ { "idx": 0, "name": "0", "path": "", "type": "sentence_transformers.models.Transformer" }, { "idx": 1, "name": "1", "path": "1_Pooling", "type": "sentence_transformers.models.Pooling" } ]
