Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
Generated from Trainer
dataset_size:3485841
loss:CachedMultipleNegativesRankingLoss
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use NbAiLab/borealis-embed-212m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NbAiLab/borealis-embed-212m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NbAiLab/borealis-embed-212m") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 293 Bytes
2ae20a7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"backend": "tokenizers",
"bos_token": "<s>",
"cls_token": "<cls>",
"eos_token": "</s>",
"is_local": false,
"local_files_only": false,
"mask_token": "<mask>",
"model_max_length": 8192,
"pad_token": "<pad>",
"tokenizer_class": "TokenizersBackend",
"unk_token": "<unk>"
}
|