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 mehdi20002/result_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mehdi20002/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mehdi20002/result_model") sentences = [ "A couple play in the tide with their young son.", "The family is outside.", "A couple are playing frisbee with a young child at the beach.", "Two adults swimming in water" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 776c3c804ad482ea444c166bc12d8c0c3e0ce710341438796a13da436cd209a0
- Size of remote file:
- 5.52 kB
- SHA256:
- 56bbc738a25b9a65989985d7fda5cdfa7a06e7b1df0ff997435cb7a853f6c68a
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