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AI4Protein
/
deep_bpe_200

Feature Extraction
Transformers
PyTorch
roformer
fill-mask
Model card Files Files and versions
xet
Community
3

Instructions to use AI4Protein/deep_bpe_200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AI4Protein/deep_bpe_200 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="AI4Protein/deep_bpe_200")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("AI4Protein/deep_bpe_200")
    model = AutoModelForMaskedLM.from_pretrained("AI4Protein/deep_bpe_200")
  • Notebooks
  • Google Colab
  • Kaggle
deep_bpe_200
344 MB
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  • 3 contributors
History: 5 commits
tyang816's picture
tyang816
nielsr's picture
nielsr HF Staff
Add model card (#2)
6a9e9e2 verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    532 Bytes
    Add model card (#2) about 1 year ago
  • config.json
    700 Bytes
    Upload RoFormerForMaskedLM over 2 years ago
  • generation_config.json
    111 Bytes
    Upload RoFormerForMaskedLM over 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    344 MB
    xet
    Upload RoFormerForMaskedLM over 2 years ago
  • special_tokens_map.json
    173 Bytes
    Upload tokenizer over 2 years ago
  • tokenizer.json
    8.02 kB
    Upload tokenizer over 2 years ago
  • tokenizer_config.json
    146 Bytes
    Upload tokenizer over 2 years ago