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MLRS
/
BERTu

Fill-Mask
Transformers
PyTorch
Safetensors
Maltese
bert
Eval Results (legacy)
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use MLRS/BERTu with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="MLRS/BERTu")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("MLRS/BERTu")
    model = AutoModelForMaskedLM.from_pretrained("MLRS/BERTu")
  • Notebooks
  • Google Colab
  • Kaggle
BERTu
1.01 GB
Ctrl+K
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  • 2 contributors
History: 8 commits
KurtMica's picture
KurtMica
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#1)
0d4fbc3 almost 3 years ago
  • .gitattributes
    1.27 kB
    Adding `safetensors` variant of this model (#1) almost 3 years ago
  • README.md
    2.91 kB
    DeepLo 2022 citation. almost 4 years ago
  • config.json
    652 Bytes
    add model about 4 years ago
  • model.safetensors
    504 MB
    xet
    Adding `safetensors` variant of this model (#1) almost 3 years ago
  • pytorch_model.bin
    504 MB
    xet
    add model about 4 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer about 4 years ago
  • tokenizer.json
    807 kB
    add tokenizer about 4 years ago
  • tokenizer_config.json
    380 Bytes
    add tokenizer about 4 years ago
  • vocab.txt
    401 kB
    add tokenizer about 4 years ago