Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:6500
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use nanalysenko/panacea_v2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nanalysenko/panacea_v2.1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nanalysenko/panacea_v2.1") sentences = [ "Цитологическое исследование пунктата кожи", "Цитологическая диагностика поражения кожи, исследование соскобов и отпечатков эрозий, ран, свищей", "Панель аллергенов деревьев № 2 IgE (клен ясенелистный, тополь, вяз, дуб, пекан),", "Панель аллергенов деревьев № 1 IgE (клен ясенелистный, береза, вяз, дуб, грецкий орех)," ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 229 Bytes
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