Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:5748
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use sangambhamare/MarathiSentenceSimilarity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sangambhamare/MarathiSentenceSimilarity with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sangambhamare/MarathiSentenceSimilarity") sentences = [ "त्याला पकडण्याचा त्यांचा कोणताही हेतू नव्हता.", "- मी असे म्हटले नाही की त्याने त्याला पकडण्याचा विचार केला.", "पॅलेस्टाईन नेतृत्व फताह-हमास दोहा कराराला पाठिंबा देते", "एक माणूस गोंधळ टेबलवर लॅपटॉप संगणक पहात बसला." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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