Sentence Similarity
sentence-transformers
Safetensors
Spanish
bert
feature-extraction
bne
entity-linking
spanish
cultural-heritage
Eval Results (legacy)
text-embeddings-inference
Instructions to use hsilvosa/bne-biencoder-entity-linker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hsilvosa/bne-biencoder-entity-linker with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hsilvosa/bne-biencoder-entity-linker") sentences = [ "Esa es una persona feliz", "Ese es un perro feliz", "Esa es una persona muy feliz", "Hoy es un día soleado" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "SentenceTransformer", | |
| "__version__": { | |
| "sentence_transformers": "5.2.0", | |
| "transformers": "4.56.2", | |
| "pytorch": "2.8.0+cu129" | |
| }, | |
| "prompts": { | |
| "query": "", | |
| "document": "" | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |