Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:2594692
loss:CachedMultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use ShiniChien/SpouseBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ShiniChien/SpouseBERT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ShiniChien/SpouseBERT") sentences = [ "George Lambert", "mary anne sievers 26/07/1855", "joseph-francois baudelaire 07/06/1759", "hoàng Tenmu" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "__version__": { | |
| "pytorch": "2.12.0+cu130", | |
| "sentence_transformers": "5.5.1", | |
| "transformers": "5.9.0" | |
| }, | |
| "default_prompt_name": null, | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "document": "", | |
| "query": "" | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |