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diarsabri
/
LaDPR-context-encoder

Feature Extraction
Transformers
PyTorch
dpr
Model card Files Files and versions
xet
Community
1

Instructions to use diarsabri/LaDPR-context-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use diarsabri/LaDPR-context-encoder with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="diarsabri/LaDPR-context-encoder")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("diarsabri/LaDPR-context-encoder")
    model = AutoModel.from_pretrained("diarsabri/LaDPR-context-encoder")
  • Notebooks
  • Google Colab
  • Kaggle
LaDPR-context-encoder
1.89 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
Diar
re-trained again
e1b5d06 about 5 years ago
  • .gitattributes
    690 Bytes
    initial commit about 5 years ago
  • README.md
    63 Bytes
    Create README.md about 5 years ago
  • config.json
    854 Bytes
    lm2 about 5 years ago
  • pytorch_model.bin
    1.88 GB
    xet
    re-trained again about 5 years ago
  • special_tokens_map.json
    112 Bytes
    lm2 about 5 years ago
  • tokenizer_config.json
    603 Bytes
    lm2 about 5 years ago
  • vocab.txt
    5.22 MB
    lm2 about 5 years ago