Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:5375
loss:OnlineContrastiveLoss
text-embeddings-inference
Instructions to use raphamendes00/carros-br-raphael-v10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use raphamendes00/carros-br-raphael-v10 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("raphamendes00/carros-br-raphael-v10") sentences = [ "Tucson 2.0L 2008 - 2011", "HB20 NOVA GERAÇÃO 1.0 2020 - 2024", "CRETA 1.0L TGDI - 2025 - 2026", "KONA - EV - ELÉTRICO" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K