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microsoft
/
longcoder-base

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

Instructions to use microsoft/longcoder-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use microsoft/longcoder-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="microsoft/longcoder-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("microsoft/longcoder-base")
    model = AutoModel.from_pretrained("microsoft/longcoder-base")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
longcoder-base
600 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
codebert's picture
codebert
Upload 7 files
d7ce267 almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit almost 3 years ago
  • config.json
    922 Bytes
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  • merges.txt
    444 kB
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  • pytorch_model.bin
    598 MB
    xet
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  • special_tokens_map.json
    957 Bytes
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  • tokenizer_config.json
    1.38 kB
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  • training_args.bin
    1.39 kB
    xet
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  • vocab.json
    1.04 MB
    Upload 7 files almost 3 years ago