Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
dense
Generated from Trainer
dataset_size:8481
loss:OnlineContrastiveLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use Fallovski/PharmAfiyahProducts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Fallovski/PharmAfiyahProducts with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Fallovski/PharmAfiyahProducts") sentences = [ "METFORMIN DENK 500MG B/30", "DUCRAY EXTRA DX AP SHP PP 200", "PULSATILLA GRAN. 7CH", "METFORMIN DENK B/30 500MG" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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