Sentence Similarity
sentence-transformers
PyTorch
English
deberta-v2
feature-extraction
dataset_size:100K<n<1M
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use bobox/DeBERTaV3-xSmall-SentenceTransformer-0.03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bobox/DeBERTaV3-xSmall-SentenceTransformer-0.03 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bobox/DeBERTaV3-xSmall-SentenceTransformer-0.03") sentences = [ "No, monsieur.", "Yes, sir.", "Look, there's a legend here.", "All models are subject to analysis." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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