Sentence Similarity
sentence-transformers
PyTorch
bert
feature-extraction
Generated from Trainer
dataset_size:2400
loss:TripletLoss
loss:MultipleNegativesRankingLoss
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use ostoveland/test3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ostoveland/test3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ostoveland/test3") 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
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:88d89aaea7513ff137050e0af105915c770c52a3c33cfea6a84587921488d664
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size 470637416
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