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
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
Download config_sentence_transformers.json from NbAiLab/nb-sbert-v2-large: direct link, hf CLI and curl.
- Browser
- Download file 285 Bytes
-
https://huggingface.co/NbAiLab/nb-sbert-v2-large/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://NbAiLab/nb-sbert-v2-large/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/NbAiLab/nb-sbert-v2-large/resolve/main/config_sentence_transformers.json
285 Bytes
| { | |
| "model_type": "SentenceTransformer", | |
| "__version__": { | |
| "sentence_transformers": "5.3.0", | |
| "transformers": "4.57.3", | |
| "pytorch": "2.9.1+rocm6.4" | |
| }, | |
| "prompts": { | |
| "query": "", | |
| "document": "" | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |