Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

mgh6
/
proBERT

Fill-Mask
Transformers
PyTorch
TensorBoard
bert
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use mgh6/proBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mgh6/proBERT with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="mgh6/proBERT")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("mgh6/proBERT")
    model = AutoModelForMaskedLM.from_pretrained("mgh6/proBERT")
  • Notebooks
  • Google Colab
  • Kaggle
proBERT / runs
13.9 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 10 commits
mgh6's picture
mgh6
Training in progress, step 4500
9fb9988 almost 3 years ago
  • Aug03_18-03-32_c24480fa43e0
    Training in progress, step 500 almost 3 years ago
  • Aug03_18-15-05_c24480fa43e0
    Training in progress, step 500 almost 3 years ago
  • Aug03_18-15-15_c24480fa43e0
    Training in progress, step 500 almost 3 years ago
  • Aug03_18-16-45_c24480fa43e0
    Training in progress, step 500 almost 3 years ago
  • Aug03_18-32-26_c24480fa43e0
    Training in progress, step 4500 almost 3 years ago