library_name: transformers datasets:

• umarigan/all_nli_tr language:
• tr pipeline_tag: sentence-similarity

模型ID说明文档

pip install -U sentence-transformers

加载模型并运行推理。

from sentence_transformers import SentenceTransformer

# 从🤗 Hub下载模型
model = SentenceTransformer("umarigan/distilbert-turkish-sentence-similarity")
# 运行推理
sentences = [
    '今年我们将去安塔利亚度假。',
    '夏天我们将在安塔利亚度假。'
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [2, 768]

# 获取嵌入向量的相似度分数
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [2, 2]