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:
- fd8b244b613f7189b1547758d849817b284f0f3ae52113a915789f927ee4b164
- Size of remote file:
- 17.1 MB
- SHA256:
- 3a56def25aa40facc030ea8b0b87f3688e4b3c39eb8b45d5702b3a1300fe2a20
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