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AI4Protein
/
ProPrime_650M_OGT_Prediction

Feature Extraction
Transformers
Safetensors
ProPrime
custom_code
Model card Files Files and versions
xet
Community

Instructions to use AI4Protein/ProPrime_650M_OGT_Prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AI4Protein/ProPrime_650M_OGT_Prediction with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="AI4Protein/ProPrime_650M_OGT_Prediction", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("AI4Protein/ProPrime_650M_OGT_Prediction", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ProPrime_650M_OGT_Prediction
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  • 1 contributor
History: 37 commits
GinnM's picture
GinnM
Update config.json
91490f9 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    470 Bytes
    Upload README.md with huggingface_hub about 2 years ago
  • config.json
    930 Bytes
    Update config.json over 1 year ago
  • configuration_proprime.py
    1.85 kB
    Upload config about 2 years ago
  • model.safetensors
    2.68 GB
    xet
    Upload ProPrimeForPretraining about 2 years ago
  • modeling_proprime.py
    51.3 kB
    Upload ProPrimeForPretraining about 2 years ago
  • special_tokens_map.json
    695 Bytes
    Upload tokenizer about 2 years ago
  • tokenization_proprime.py
    4.92 kB
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    1.24 kB
    Upload tokenizer about 2 years ago
  • vocab.txt
    93 Bytes
    Upload tokenizer about 2 years ago