Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:33
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use zxcvo/product-search-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use zxcvo/product-search-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("zxcvo/product-search-model") sentences = [ "Áo Polo Lacoste với chất liệu Petit Piqué và thiết kế cổ gập kinh điển", "Giày cao gót đẳng cấp", "Xe điều khiển từ xa", "Áo polo sang trọng" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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