Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:84000
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use HoshinoSSR/m3e_doctor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HoshinoSSR/m3e_doctor with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HoshinoSSR/m3e_doctor") sentences = [ "痔疮外痔请问真么办吃什么药", "初步考虑你是否有腰肌劳损或是腰间盘的突出等,这些疾病都可以引起的腰部臀部的不适,或是牵扯到大腿部位。建议你到医院做个全面的检查,比如做个腰部的CT,MRI,看看有无腰肌的损伤或是看看有无椎间盘的突出,导致神经的压迫压迫等,明确诊断,积极治疗,止疼。还可以做个电解质的检查,看看有无缺钙等", "可尝试使用内塞栓剂和口服片剂联合用药的方案,如麝香痔疮栓加痔炎消片。而对于肿痛症状明显者,可在上述用药之前,先进行局部熏洗,可减轻肛门肿胀症状、缓解疼痛。应用较多的是,金玄痔科熏洗散。必要时再考虑手术治疗。无论是手术,还是药物,痔疮都不能彻底治愈。因此,通过治疗痔疮症状消除后,在生活习惯上也要有改变,尽量少熬夜,吃辛辣上火食物的次数尽量少点。如果原来不太爱吃水果,现在就要强迫自己多吃水果,因为水果对便秘的预防和消除都非常好,而痔疮的导火线很可能是便秘。", "这个一般在一年左右时间,希望我的回答能帮到你。" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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