Sentence Similarity
sentence-transformers
Safetensors
distilbert
feature-extraction
dense
Generated from Trainer
dataset_size:3324
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use roig/compass-product-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use roig/compass-product-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("roig/compass-product-classifier") sentences = [ "Pizarra acústica de guitarra Dunlop T213C negra - Top plate de reemplazo para guitarras acústicas, fabricada en madera maciza (arce), con perforaciones para mejor resonancia y acabado negro mate", "Accesorios para instrumentos musicales / Musical instrument accessories", "Personal Care / Aseo", "Sistema limpiaparabrisas / Windshield wiper system" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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