Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
Generated from Trainer
dataset_size:25012
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use alpcansoydas/product-model-02.12.25-total46clas-ifhavemorethan100sampleperclass-0.71acc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alpcansoydas/product-model-02.12.25-total46clas-ifhavemorethan100sampleperclass-0.71acc with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alpcansoydas/product-model-02.12.25-total46clas-ifhavemorethan100sampleperclass-0.71acc") sentences = [ "ÇİFT KLİMALI BARAN FREE COOLING UNIT MONTAJ KITI.", "Building construction machinery and accessories", "Building construction machinery and accessories", "Mounting Hardware" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle