text2vec-base-chinese

pip install -U text2vec

from text2vec import SentenceModel
sentences = ['如何更换花呗绑定银行卡', '花呗更改绑定银行卡']

model = SentenceModel('shibing624/text2vec-base-chinese')
embeddings = model.encode(sentences)
print(embeddings)

pip install transformers

pip install -U sentence-transformers

from sentence_transformers import SentenceTransformer

m = SentenceTransformer("shibing624/text2vec-base-chinese")
sentences = ['如何更换花呗绑定银行卡', '花呗更改绑定银行卡']

sentence_embeddings = m.encode(sentences)
print("Sentence embeddings:")
print(sentence_embeddings)

# pip install 'optimum[openvino]'

from sentence_transformers import SentenceTransformer

model = SentenceTransformer(
    "shibing624/text2vec-base-chinese",
    backend="openvino",
)

embeddings = model.encode(["如何更换花呗绑定银行卡", "花呗更改绑定银行卡", "你是谁"])
print(embeddings.shape)
similarities = model.similarity(embeddings, embeddings)
print(similarities)

# pip install optimum
from sentence_transformers import SentenceTransformer

model = SentenceTransformer(
    "shibing624/text2vec-base-chinese",
    backend="onnx",
    model_kwargs={"file_name": "model_qint8_avx512_vnni.onnx"},
)
embeddings = model.encode(["如何更换花呗绑定银行卡", "花呗更改绑定银行卡", "你是谁"])
print(embeddings.shape)
similarities = model.similarity(embeddings, embeddings)
print(similarities)