Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
feature-extraction
Generated from Trainer
dataset_size:8066634
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Parallia/Fairly-Multilingual-ModernBERT-Embed-BE-EN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Parallia/Fairly-Multilingual-ModernBERT-Embed-BE-EN with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Parallia/Fairly-Multilingual-ModernBERT-Embed-BE-EN") sentences = [ "These three mysterious men came to our help.", "Three strange guys helped us then.", "These three black birds came in our garden.", "Some people are helpful.", "One, two, three... Who can guess the next digits?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [5, 5] - Notebooks
- Google Colab
- Kaggle
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