Sentence Similarity
sentence-transformers
Safetensors
distilbert
feature-extraction
dense
Generated from Trainer
dataset_size:50000
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use abubin12599/distiluse-base-multilingual-cased-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use abubin12599/distiluse-base-multilingual-cased-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("abubin12599/distiluse-base-multilingual-cased-v2") sentences = [ "pollybiddut gazipur", "gazipur kaliakair pollybiddut", "naogaon atrai mirjapur bazar", "dhaka north khilkhet khilkhet" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K