Feature Extraction
sentence-transformers
Safetensors
xlm-roberta
datadreamer
datadreamer-0.35.0
Synthetic
sentence-similarity
text-embeddings-inference
Instructions to use StyleDistance/mstyledistance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use StyleDistance/mstyledistance with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("StyleDistance/mstyledistance") sentences = [ "彼は技術的な複雑さと格闘し、彼の作品は驚くべき視覚的緊張を生み出した。", "Serviste mariscos frescos en el condado de Middlesex y áreas circundantes.", "Él sirvió mariscos frescos en el condado de Middlesex y áreas circundantes." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b0b15af9a386dacc58ab9106a95ee04bff1ee7610ec1676675f5cd3c3f98c30
- Size of remote file:
- 556 MB
- SHA256:
- 57827687b77bd6aba053f9b29c37d68aee340792d2106f0586d4f82f3179cb02
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