Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:1200
loss:OnlineContrastiveLoss
text-embeddings-inference
Instructions to use raphamendes00/carros-br-raphael-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use raphamendes00/carros-br-raphael-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("raphamendes00/carros-br-raphael-v2") sentences = [ "HB20 1.6 PREMIUM AT", "NOVO HB20 + R spec 1.6 2016 - 2017 - 2018 - 2019 - 2020 - 2021 - 2022 -2023", "HB20 1.6 2012 - 2013 - 2014 - 2015", "NOVO HB20 + R spec 1.6 2016 - 2017 - 2018 - 2019 - 2020 - 2021 - 2022 -2023" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K