Sentence Similarity
sentence-transformers
Safetensors
English
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:80
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use SamiKazrboubi/result_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SamiKazrboubi/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SamiKazrboubi/result_model") sentences = [ "A man, woman, and child enjoying themselves on a beach.", "A family of three is at the mall shopping.", "An actress and her favorite assistant talk a walk in the city.", "The woman is nake." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle