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EVAMLab
/
apoha-bge-small-en-v1.5

Text Classification
sentence-transformers
Safetensors
English
bert
out-of-distribution-detection
few-shot-learning
neuro-symbolic
buddhist-logic
safety
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use EVAMLab/apoha-bge-small-en-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use EVAMLab/apoha-bge-small-en-v1.5 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("EVAMLab/apoha-bge-small-en-v1.5")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Notebooks
  • Google Colab
  • Kaggle
apoha-bge-small-en-v1.5
134 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 8 commits
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alexanderkhundoev
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  • .gitattributes
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  • LICENSE
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  • README.md
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  • concepts.json
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  • config.json
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  • config_sentence_transformers.json
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  • model.safetensors
    133 MB
    xet
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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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  • training_info.json
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