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
Update README.md
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README.md
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@@ -47,8 +47,8 @@ from sentence_transformers.util import cos_sim
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model = SentenceTransformer('StyleDistance/mstyledistance') # Load model
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input = model.encode("
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others = model.encode(["
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print(cos_sim(input, others))
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```
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model = SentenceTransformer('StyleDistance/mstyledistance') # Load model
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input = model.encode("ÉL TIENE PROBLEMAS PARA LOGRAR LA TEMPERATURA ADECUADA PARA COCINAR LA GALLINA CORNISH.")
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others = model.encode(["TOCARÁS LA GUITARRA CON TU AMIGO; SERÁ UNA EXCELENTE OPORTUNIDAD PARA MEJORAR TUS HABILIDADES MUSICALES.", "Él tiene problemas para lograr la temperatura adecuada para cocinar la gallina Cornish."])
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print(cos_sim(input, others))
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```
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