Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:80
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use Riyadh03/result_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Riyadh03/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Riyadh03/result_model") sentences = [ "A couple play in the tide with their young son.", "The family is outside.", "A man in a restaurant is waiting for his meal to arrive.", "Two adults walking across a road" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df4129a215149952104f90bb337a568f4c9cd7e26cf09ea5badea565457d499d
- Size of remote file:
- 5.46 kB
- SHA256:
- ed3793454249ac09153c91935ccdccdf6002b921720ebd53025cf7c59189c6b8
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