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nvidia
/
esm2_t33_650M_UR50D

Fill-Mask
Transformers
Safetensors
nv_esm
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use nvidia/esm2_t33_650M_UR50D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nvidia/esm2_t33_650M_UR50D with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="nvidia/esm2_t33_650M_UR50D", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForMaskedLM
    model = AutoModelForMaskedLM.from_pretrained("nvidia/esm2_t33_650M_UR50D", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
esm2_t33_650M_UR50D
2.6 GB
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  • 1 contributor
History: 15 commits
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pstjohn
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  • .gitattributes
    1.52 kB
    initial commit 10 months ago
  • LICENSE
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  • README.md
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  • config.json
    1.36 kB
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  • esm_nv.py
    38.6 kB
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  • model.safetensors
    2.6 GB
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  • special_tokens_map.json
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  • tokenizer.json
    2.95 kB
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  • tokenizer_config.json
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  • vocab.txt
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