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MaCoCu
/
MaltBERTa

Feature Extraction
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
Maltese
roberta
MaltBERTa
MaCoCu
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use MaCoCu/MaltBERTa with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="MaCoCu/MaltBERTa")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("MaCoCu/MaltBERTa")
    model = AutoModel.from_pretrained("MaCoCu/MaltBERTa")
  • Notebooks
  • Google Colab
  • Kaggle
MaltBERTa
1.33 GB
Ctrl+K
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  • 2 contributors
History: 6 commits
RVN's picture
RVN
Update README.md
2d14bf3 over 3 years ago
  • .gitattributes
    1.34 kB
    initial commit almost 4 years ago
  • README.md
    4.18 kB
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  • config.json
    703 Bytes
    Push model files almost 4 years ago
  • flax_model.msgpack
    442 MB
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  • merges.txt
    312 kB
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  • pytorch_model.bin

    Detected Pickle imports (4)

    • "collections.OrderedDict",
    • "torch.LongStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage"

    What is a pickle import?

    443 MB
    xet
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  • special_tokens_map.json
    772 Bytes
    Push model files almost 4 years ago
  • tf_model.h5
    443 MB
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  • tokenizer_config.json
    1.11 kB
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  • vocab.json
    525 kB
    Push model files almost 4 years ago