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digio
/
BERTweet-base_1000000s_all_MNRL

Feature Extraction
Transformers
PyTorch
roberta
Model card Files Files and versions
xet
Community
1

Instructions to use digio/BERTweet-base_1000000s_all_MNRL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use digio/BERTweet-base_1000000s_all_MNRL with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="digio/BERTweet-base_1000000s_all_MNRL")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("digio/BERTweet-base_1000000s_all_MNRL")
    model = AutoModel.from_pretrained("digio/BERTweet-base_1000000s_all_MNRL", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
BERTweet-base_1000000s_all_MNRL
540 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
digio's picture
digio
add model
9b472a4 almost 5 years ago
  • .gitattributes
    1.18 kB
    initial commit almost 5 years ago
  • config.json
    755 Bytes
    add model almost 5 years ago
  • pytorch_model.bin
    540 MB
    xet
    add model almost 5 years ago