Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:249
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use raphamendes00/carros-br-raphael-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use raphamendes00/carros-br-raphael-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("raphamendes00/carros-br-raphael-v1") sentences = [ "vera cruz 3.8l 2008 - 2013", "novo hb20 1.0 2016 - 2017 - 2018 - 2019", "hb20 x 2016 - 2017 - 2018 - 2019- 2020 - 2021 - 2022 -2023", "vera cruz 3.8l 2008 - 2013" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K