Sentence Similarity
sentence-transformers
Safetensors
English
distilbert
feature-extraction
Generated from Trainer
dataset_size:404290
loss:OnlineContrastiveLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use yahyaabd/stsb-distilbert-base-ocl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yahyaabd/stsb-distilbert-base-ocl with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yahyaabd/stsb-distilbert-base-ocl") sentences = [ "What does the lock symbol on my iPhone 6 means?", "How did the Soviet Navy compare to the US Navy?", "What does the iPhone icon with lock and arrow mean?", "What is the importance of electrical engineering?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "__version__": { | |
| "sentence_transformers": "3.4.0", | |
| "transformers": "4.48.1", | |
| "pytorch": "2.5.1+cu124" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |