Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:123565
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use Maksim-KOS/multilingual-e5-large-instruct-saturn-planet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Maksim-KOS/multilingual-e5-large-instruct-saturn-planet with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Maksim-KOS/multilingual-e5-large-instruct-saturn-planet") sentences = [ "Валик войлочный 5мм 100мм 2шт", "Труба водосточная, металл, d=90 мм, белый, 3 м", "Мини-валик Варяг 31877 войлочный, ворс 5 мм, 100 мм (уп. 2 шт.)", "Валик Варяг 31862, велюр ворс 5 мм, 250 мм" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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