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facebook
/
esm2_t30_150M_UR50D

Fill-Mask
Transformers
PyTorch
google-tensorflow TensorFlow
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esm
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xet
Community
4

Instructions to use facebook/esm2_t30_150M_UR50D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use facebook/esm2_t30_150M_UR50D with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="facebook/esm2_t30_150M_UR50D")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("facebook/esm2_t30_150M_UR50D")
    model = AutoModelForMaskedLM.from_pretrained("facebook/esm2_t30_150M_UR50D")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
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TemporalMesh Transformer: 29.4 PPL at 48% compute — beats Mamba, new open-source architecture

#5 opened 3 days ago by
vigneshwar234

[AUTOMATED] Model Memory Requirements

#3 opened over 2 years ago by
model-sizer-bot
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