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recursionpharma
/
OpenPhenom

Feature Extraction
Transformers
Safetensors
MAE
custom_code
Model card Files Files and versions
xet
Community
23

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

  • Libraries
  • Transformers

    How to use recursionpharma/OpenPhenom with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="recursionpharma/OpenPhenom", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("recursionpharma/OpenPhenom", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
OpenPhenom
48.6 kB
Ctrl+K
Ctrl+K
  • 4 contributors
History: 9 commits
kiankaydee's picture
kiankaydee
dump
373b8b8 about 2 years ago
  • .vscode
    some baseline code for the repo over 2 years ago
  • LICENSE
    19.3 kB
    Create NCCL 4.0 LICENSE over 2 years ago
  • README.md
    1.75 kB
    dump code about 2 years ago
  • config.yaml
    424 Bytes
    dump about 2 years ago
  • loss.py
    2.13 kB
    dump about 2 years ago
  • mae_modules.py
    9.38 kB
    dump about 2 years ago
  • mae_utils.py
    2.2 kB
    dump about 2 years ago
  • masking.py
    1.61 kB
    dump about 2 years ago
  • requirements.txt
    171 Bytes
    fix reqs about 2 years ago
  • vit.py
    9.65 kB
    dump about 2 years ago
  • vit_encoder.py
    1.93 kB
    some baseline code for the repo over 2 years ago