Sentence Similarity
sentence-transformers
PyTorch
bert
feature-extraction
Generated from Trainer
dataset_size:400
loss:TripletLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use ostoveland/test7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ostoveland/test7 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ostoveland/test7") sentences = [ "query: Ny duk til markise på verandaen.", "query: Boring og sprenging fjell", "query: Solskjerming Duette gardiner", "query: Bygge ark" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
Browse filesThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to `pytorch_model.bin` but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
- model.safetensors +3 -0
model.safetensors
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