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imaneb942
/
MNLP_M3_document_encoder

Feature Extraction
Transformers
PyTorch
ONNX
Safetensors
OpenVINO
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use imaneb942/MNLP_M3_document_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use imaneb942/MNLP_M3_document_encoder with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="imaneb942/MNLP_M3_document_encoder")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("imaneb942/MNLP_M3_document_encoder")
    model = AutoModel.from_pretrained("imaneb942/MNLP_M3_document_encoder")
  • Notebooks
  • Google Colab
  • Kaggle
MNLP_M3_document_encoder / openvino
1.68 GB
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  • 1 contributor
History: 1 commit
imaneb942's picture
imaneb942
Upload 4 files
16bc4ed verified 11 months ago
  • openvino_model.bin
    1.34 GB
    xet
    Upload 4 files 11 months ago
  • openvino_model.xml
    732 kB
    Upload 4 files 11 months ago
  • openvino_model_qint8_quantized.bin
    337 MB
    xet
    Upload 4 files 11 months ago
  • openvino_model_qint8_quantized.xml
    1.35 MB
    Upload 4 files 11 months ago