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MLMvsCLM
/
610m-clm-12k

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

Instructions to use MLMvsCLM/610m-clm-12k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MLMvsCLM/610m-clm-12k with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="MLMvsCLM/610m-clm-12k", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("MLMvsCLM/610m-clm-12k", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
610m-clm-12k
3.04 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
hgissbkh's picture
hgissbkh
Upload config
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  • .gitattributes
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  • README.md
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  • config.json
    1.26 kB
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  • configuration_sl_model.py
    9.62 kB
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  • modeling_sl_model.py
    42.7 kB
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    3.02 GB
    xet
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  • special_tokens_map.json
    121 Bytes
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  • tokenizer.json
    17.2 MB
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  • tokenizer_config.json
    55.4 kB
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