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wesley7137
/
codebertDM

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

Instructions to use wesley7137/codebertDM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use wesley7137/codebertDM with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="wesley7137/codebertDM")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("wesley7137/codebertDM")
    model = AutoModel.from_pretrained("wesley7137/codebertDM", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
codebertDM
3.5 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 8 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
6ab1ed9 verified over 1 year ago
  • checkpoint-44500
    Delete checkpoint-44500/config.json about 3 years ago
  • .gitattributes
    1.52 kB
    initial commit about 3 years ago
  • config.json
    698 Bytes
    Update config.json about 3 years ago
  • generation_config.json
    132 Bytes
    Upload 11 files about 3 years ago
  • model.safetensors
    499 MB
    xet
    Adding `safetensors` variant of this model over 1 year ago
  • optimizer.pt
    998 MB
    xet
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  • pytorch_model.bin
    499 MB
    xet
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  • rng_state.pth
    14.6 kB
    xet
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  • scheduler.pt
    627 Bytes
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  • tokenizer.json
    2.11 MB
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  • tokenizer_config.json
    1.78 kB
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  • trainer_state.json
    448 kB
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  • training_args.bin
    3.9 kB
    xet
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  • vocab.json
    798 kB
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