Sentence Similarity
sentence-transformers
PyTorch
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:2400
loss:TripletLoss
loss:MultipleNegativesRankingLoss
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use ostoveland/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ostoveland/test2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ostoveland/test2") sentences = [ "oppgradering av sikringsskap med nye sikringer", "query: pipearbeid i kjeller", "query: utskifting av sikringer i sikringsskap", "query: arkitekttegning av tilbygg" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24550daf620088379304271a4c64e376c5db026792d451e57905727464eb9e86
- Size of remote file:
- 1.11 GB
- SHA256:
- 96c78d2c1c0cadd56c687fbfd6f2e046da4159f9f950658fee6df595365775d8
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