Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:80415
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use lingtrain/labse-kalmyk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lingtrain/labse-kalmyk with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lingtrain/labse-kalmyk") sentences = [ "Зуг эрднь-ишин силос келһнә , нань чигн кергүднь бас дегц дарцлдад , тәв һарсн наста агрономд дав деерән цагнь беркдҗ бәәхнь Долдад медгднә . ", "быть товарищем", "Дола понимала , что агроному не так-то просто в эту страдную пору выкроить время . В связи с уборкой на него обрушилось множество забот . ", "стеснение" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K