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Motahar
/
dummy-model

Feature Extraction
Transformers
PyTorch
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use Motahar/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Motahar/dummy-model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Motahar/dummy-model")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Motahar/dummy-model")
    model = AutoModel.from_pretrained("Motahar/dummy-model")
  • Notebooks
  • Google Colab
  • Kaggle
dummy-model
434 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Motahar's picture
Motahar
First commit
c06e3fa over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • config.json
    656 Bytes
    First commit over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    433 MB
    xet
    First commit over 4 years ago
  • special_tokens_map.json
    112 Bytes
    First commit over 4 years ago
  • tokenizer.json
    436 kB
    First commit over 4 years ago
  • tokenizer_config.json
    320 Bytes
    First commit over 4 years ago
  • vocab.txt
    213 kB
    First commit over 4 years ago