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NbAiLab
/
nb-sbert-v2-large

Sentence Similarity
sentence-transformers
Safetensors
Norwegian
bert
feature-extraction
dense
Generated from Trainer
dataset_size:527098
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
🇪🇺 Region: EU
Model card Files Files and versions
xet
Community

Instructions to use NbAiLab/nb-sbert-v2-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use NbAiLab/nb-sbert-v2-large with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("NbAiLab/nb-sbert-v2-large")
    
    sentences = [
        "The man talked to a girl over the internet camera.",
        "A group of elderly people pose around a dining table.",
        "A teenager talks to a girl over a webcam.",
        "There is no 'still' that is not relative to some other object."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
nb-sbert-v2-large / 1_Pooling
Ctrl+K
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  • 3 contributors
History: 1 commit
vlhandfo's picture
vlhandfo
Upload model files
c0b7d31 about 1 month ago
  • config.json
    313 Bytes
    Upload model files about 1 month ago