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Ehsanl
/
cncpt_e5

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:295188
loss:WeightedMultiPositiveCachedLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Ehsanl/cncpt_e5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Ehsanl/cncpt_e5 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Ehsanl/cncpt_e5")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
cncpt_e5
2.26 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Ehsanl's picture
Ehsanl
Update README.md
1997bc7 verified about 8 hours ago
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  • .gitattributes
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  • README.md
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  • concept_channel.json
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  • config.json
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  • config_sentence_transformers.json
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  • dev_by_kind.json
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  • model.safetensors
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  • modules.json
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  • sentence_bert_config.json
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  • tokenizer.json
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  • tokenizer_config.json
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