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McGill-NLP
/
dpr-statcan-conversation_encoder-title

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

Instructions to use McGill-NLP/dpr-statcan-conversation_encoder-title with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use McGill-NLP/dpr-statcan-conversation_encoder-title with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="McGill-NLP/dpr-statcan-conversation_encoder-title")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("McGill-NLP/dpr-statcan-conversation_encoder-title")
    model = AutoModel.from_pretrained("McGill-NLP/dpr-statcan-conversation_encoder-title")
  • Notebooks
  • Google Colab
  • Kaggle
dpr-statcan-conversation_encoder-title
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  • 2 contributors
History: 3 commits
xhluca's picture
xhluca
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#1)
f9e683f almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • config.json
    665 Bytes
    Upload with huggingface_hub about 3 years ago
  • model.safetensors
    438 MB
    xet
    Adding `safetensors` variant of this model (#1) almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.LongStorage",
    • "torch.FloatStorage"

    What is a pickle import?

    438 MB
    xet
    Upload with huggingface_hub about 3 years ago