Sentence Similarity
sentence-transformers
PyTorch
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:24000
loss:TripletLoss
loss:MultipleNegativesRankingLoss
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use ostoveland/test9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ostoveland/test9 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ostoveland/test9") sentences = [ "Fjerne trapp i mur utvendig", "query: Montere nytt dusjkabinett", "query: installasjon av beslag på portaldører", "query: fjerne utvendig trapp i mur" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened 11 months ago
by
SFconvertbot