Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Norwegian
bert
feature-extraction
text-embeddings-inference
Instructions to use NbAiLab/nb-sbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NbAiLab/nb-sbert-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NbAiLab/nb-sbert-base") sentences = [ "This is a Norwegian boy", "Dette er en norsk gutt", "This is an English boy", "This is a dog" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use NbAiLab/nb-sbert-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("NbAiLab/nb-sbert-base") model = AutoModel.from_pretrained("NbAiLab/nb-sbert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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- feature-extraction
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- sentence-similarity
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- transformers
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widget:
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- source_sentence: "That is a xxx person"
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sentences:
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- "That is a happy dog"
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- "That is a very happy person"
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- "Today is a sunny day"
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example_title: "Happy"
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