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Bheri
/
e5large-en-sa-v1

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
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/e5large-en-sa-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Bheri/e5large-en-sa-v1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Bheri/e5large-en-sa-v1")
    
    sentences = [
        "Wherever and whenever they saw any creature, any dweller of the Khandava, escaping from the fire, those two great heroes immediately shot it down.",
        "वयं पठाम ।",
        "दि अमोङ्ग- अस् कुक्कुटस्य खण्डः पैरेडोलिया इत्यस्य उदाहरणम् अस्ति।\n",
        "यत्र यत्र च दृश्यन्ते प्राणिनः खाण्डवालयाः। पलायन्तः प्रवीरौ तौ तत्र तत्राभ्यधावताम्॥"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
e5large-en-sa-v1 / eval
372 Bytes
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
saikasyap's picture
saikasyap
Initial commit
8e0e716 verified 10 months ago
  • translation_evaluation_eval-en-sa_results.csv
    372 Bytes
    Initial commit 10 months ago