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WeightWatcher
/
albert-large-v2-rte

Text Classification
Transformers
PyTorch
English
albert
Model card Files Files and versions
xet
Community
1

Instructions to use WeightWatcher/albert-large-v2-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use WeightWatcher/albert-large-v2-rte with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="WeightWatcher/albert-large-v2-rte")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("WeightWatcher/albert-large-v2-rte")
    model = AutoModelForSequenceClassification.from_pretrained("WeightWatcher/albert-large-v2-rte")
  • Notebooks
  • Google Colab
  • Kaggle
albert-large-v2-rte
73.8 MB
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  • 1 contributor
History: 5 commits
cdhinrichs's picture
cdhinrichs
Updated model card to reflect new owner
eef9f5c almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    2.57 kB
    Updated model card to reflect new owner almost 3 years ago
  • config.json
    1.06 kB
    Added a model and config almost 3 years ago
  • eval_results.json
    163 Bytes
    Added a model and config almost 3 years ago
  • pytorch_model.bin
    70.8 MB
    xet
    Added a model and config almost 3 years ago
  • special_tokens_map.json
    286 Bytes
    Added tokenizer configs almost 3 years ago
  • spiece.model
    760 kB
    xet
    Added tokenizer configs almost 3 years ago
  • tokenizer.json
    2.27 MB
    Added tokenizer configs almost 3 years ago
  • tokenizer_config.json
    527 Bytes
    Added tokenizer configs almost 3 years ago
  • train_results.json
    165 Bytes
    Added a model and config almost 3 years ago