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textattack
/
albert-base-v2-rotten_tomatoes

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

Instructions to use textattack/albert-base-v2-rotten_tomatoes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use textattack/albert-base-v2-rotten_tomatoes with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="textattack/albert-base-v2-rotten_tomatoes")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("textattack/albert-base-v2-rotten_tomatoes")
    model = AutoModelForMaskedLM.from_pretrained("textattack/albert-base-v2-rotten_tomatoes")
  • Notebooks
  • Google Colab
  • Kaggle
albert-base-v2-rotten_tomatoes
94.3 MB
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History: 12 commits
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SFconvertbot
Adding `safetensors` variant of this model
6e9a4b7 over 2 years ago
  • 1593060127.506348
    Update 1593060127.506348/events.out.tfevents.1593060127.qcuda1 almost 6 years ago
  • .gitattributes
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    Adding `safetensors` variant of this model over 2 years ago
  • README.md
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  • config.json
    724 Bytes
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  • events.out.tfevents.1593060127.qcuda1
    502 Bytes
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  • log.txt
    1.86 kB
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  • model.safetensors
    46.7 MB
    xet
    Adding `safetensors` variant of this model over 2 years ago
  • pytorch_model.bin
    46.7 MB
    xet
    Update pytorch_model.bin almost 6 years ago
  • special_tokens_map.json
    156 Bytes
    Update special_tokens_map.json almost 6 years ago
  • spiece.model
    760 kB
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  • tokenizer_config.json
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  • train_args.json
    782 Bytes
    Update train_args.json almost 6 years ago