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Bheri
/
ithasa-mmbert-v2

Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
dense
Generated from Trainer
dataset_size:257886
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Bheri/ithasa-mmbert-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Bheri/ithasa-mmbert-v2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Bheri/ithasa-mmbert-v2")
    
    sentences = [
        "Then bring the needle back to the back side of the fabric.",
        "अधिभूतं क्षरो भावः पुरुषश्चाधिदैवतम्। अधियज्ञोऽहमेवात्र देहे देहभृतां वर॥",
        "मराठी-चलच्चित्रे \"साव्ळी प्रेमाची\" इत्यस्मिन् सः मुख्यपात्रं निरवहत्।\n",
        "तदनन्तरं वस्त्रस्य तटे सूचिकां पृष्टे क्रियते ।"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
ithasa-mmbert-v2 / eval
394 Bytes
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
saikasyap's picture
saikasyap
Initial commit
8104a92 verified 4 months ago
  • translation_evaluation_eval-en-sa_results.csv
    394 Bytes
    Initial commit 4 months ago