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koryl
/
bge-m3-quantized-int8

Feature Extraction
sentence-transformers
PyTorch
Russian
xlm-roberta
quantization
int8
cpu-optimized
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use koryl/bge-m3-quantized-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use koryl/bge-m3-quantized-int8 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("koryl/bge-m3-quantized-int8")
    
    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
bge-m3-quantized-int8
1.38 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
koryl's picture
koryl
Upload INT8 quantized BGE-M3 model
b258f96 verified 19 days ago
  • 1_Pooling
    Upload INT8 quantized BGE-M3 model 19 days ago
  • .gitattributes
    1.57 kB
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  • README.md
    1.51 kB
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  • config.json
    774 Bytes
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  • config_sentence_transformers.json
    296 Bytes
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  • modules.json
    448 Bytes
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  • pytorch_model.bin
    1.36 GB
    xet
    Upload INT8 quantized BGE-M3 model 19 days ago
  • tokenizer.json
    17.1 MB
    xet
    Upload INT8 quantized BGE-M3 model 19 days ago
  • tokenizer_config.json
    426 Bytes
    Upload INT8 quantized BGE-M3 model 19 days ago