Sentence Similarity
sentence-transformers
PyTorch
distilbert
feature-extraction
Generated from Trainer
dataset_size:2400
loss:TripletLoss
loss:MultipleNegativesRankingLoss
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use ostoveland/test12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ostoveland/test12 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ostoveland/test12") sentences = [ "Flislegging av hall", "query: tapetsering av rom med grunnflate 4x4.5 meter minus tre dører", "query: fliser i hall", "query: fornye markiseduk" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0b0157c763a71dd6ae0b650e9279acd369ee0f2ad4dd48b3df9a694196f5dca
- Size of remote file:
- 265 MB
- SHA256:
- 8cea25e4e8c6d7f10257cb4ceda17bc37f4c083b78e1973d89fc348157f0ccda
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