Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:56574
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use johnyy212/moe-girl-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use johnyy212/moe-girl-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("johnyy212/moe-girl-v2") sentences = [ "围裙、大叔、爸爸、抽烟、上门女婿", "Royde咖啡店老板", "角色:罗丽娜\n本名:罗丽娜\n别名:萝莉娜\n发色:黑\n瞳色:红\n萌点:萝莉、傲娇、孩子气", "角色:Royde咖啡店老板\n别名:店长、老爸\n发色:银\n瞳色:琥珀\n年龄:50\n萌点:店长、大叔、爸爸、上门女婿、围裙、抽烟、妻管严" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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