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JanSt
/
gbert-base-finetuned-twitter

Fill-Mask
Transformers
PyTorch
bert
Generated from Trainer
Model card Files Files and versions
xet
Community
1

Instructions to use JanSt/gbert-base-finetuned-twitter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use JanSt/gbert-base-finetuned-twitter with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="JanSt/gbert-base-finetuned-twitter")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("JanSt/gbert-base-finetuned-twitter")
    model = AutoModelForMaskedLM.from_pretrained("JanSt/gbert-base-finetuned-twitter", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
gbert-base-finetuned-twitter
441 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 98 commits
JanSt's picture
JanSt
Merge remote-tracking branch 'origin/main'
767d87b about 3 years ago
  • .gitattributes
    1.52 kB
    initial commit about 3 years ago
  • README.md
    1.78 kB
    End of training about 3 years ago
  • config.json
    630 Bytes
    End of training about 3 years ago
  • fine_tune_mlm_twitter.py
    5.45 kB
    modularized about 3 years ago
  • generation_config.json
    90 Bytes
    End of training about 3 years ago
  • pytorch_model.bin
    440 MB
    xet
    End of training about 3 years ago
  • special_tokens_map.json
    125 Bytes
    End of training about 3 years ago
  • tokenizer.json
    729 kB
    End of training about 3 years ago
  • tokenizer_config.json
    386 Bytes
    End of training about 3 years ago
  • training_args.bin
    4.03 kB
    xet
    Training in progress, step 500 about 3 years ago
  • vocab.txt
    240 kB
    End of training about 3 years ago