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nielsr
/
lilt-xlm-roberta-base

Feature Extraction
Transformers
PyTorch
Safetensors
lilt
Model card Files Files and versions
xet
Community
10

Instructions to use nielsr/lilt-xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nielsr/lilt-xlm-roberta-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="nielsr/lilt-xlm-roberta-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("nielsr/lilt-xlm-roberta-base")
    model = AutoModel.from_pretrained("nielsr/lilt-xlm-roberta-base", device_map="auto")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

How can I get token level bounding boxes from XLMRobertaTokenizer?

#10 opened over 2 years ago by
zeroman0112

annotated dutch dataset

2
#9 opened almost 3 years ago by
Ifyouknowthenyouknow

Invoice extractor

3
#8 opened about 3 years ago by
lokaspire

How to use a different LM with LiLT?

#7 opened about 3 years ago by
edxnsn

Training Data

#6 opened over 3 years ago by
uricamic

Would it be difficult to get a xlm-roberta-large version of this model up?

1
#4 opened over 3 years ago by
marhlder

Getting TypeError: _batch_encode_plus() got an unexpected keyword argument 'boxes'

1
#1 opened over 3 years ago by
jimmyloyola
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