Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
Generated from Trainer
dataset_size:10000
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use kasraarabi/finetuned-caption-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kasraarabi/finetuned-caption-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kasraarabi/finetuned-caption-embedding") sentences = [ "an elephant with a leaf on its back", "an elephant is walking through the woods", "a white truck with a white sign on it", "a bathroom with a tub and sink" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db8692fd9e3467a212c5a3c66513fc4052354dab26ce67a72abcf7e6b5317ead
- Size of remote file:
- 438 MB
- SHA256:
- d57655bc0ec39a349554b3647c77655cbe4a57c1a7ddd65b843b11944cb9e520
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