Sentence Similarity
sentence-transformers
Safetensors
English
Catalan
mpnet
feature-extraction
dataset_size:1K<n<10K
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use pauhidalgoo/finetuned-sts-ca-mpnet-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use pauhidalgoo/finetuned-sts-ca-mpnet-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pauhidalgoo/finetuned-sts-ca-mpnet-base") sentences = [ "Dia Internacional del Nen Prematur", "Premiats a les comarques de Barcelona", "Les concordances són adjectiu / substantiu o verb / substantiu.", "Els Mossos en busquen un altre, que va aconseguir fugir en ser enxampats 'in fraganti'" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "__version__": { | |
| "sentence_transformers": "3.0.0", | |
| "transformers": "4.41.1", | |
| "pytorch": "2.3.0+cu121" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": null | |
| } |