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 MahfoudAi/result_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use MahfoudAi/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("MahfoudAi/result_model") sentences = [ "Woman in white in foreground and a man slightly behind walking with a sign for John's Pizza and Gyro in the background.", "A man and a soman are eating together at John's Pizza and Gyro.", "A high school is hosting an event.", "A family of three is at the beach." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 277 Bytes
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