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Sami92
/
XLM-PER-B

Token Classification
Transformers
PyTorch
German
Spanish
English
xlm-roberta
politics
communication
public sphere
Model card Files Files and versions
xet
Community
1

Instructions to use Sami92/XLM-PER-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Sami92/XLM-PER-B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="Sami92/XLM-PER-B")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Sami92/XLM-PER-B")
    model = AutoModelForTokenClassification.from_pretrained("Sami92/XLM-PER-B")
  • Notebooks
  • Google Colab
  • Kaggle
XLM-PER-B
1.13 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 11 commits
Sami92's picture
Sami92
Update README.md
063880c verified almost 2 years ago
  • .gitattributes
    1.57 kB
    Upload tokenizer over 2 years ago
  • README.md
    3.52 kB
    Update README.md almost 2 years ago
  • config.json
    1.29 kB
    Upload XLMRobertaForTokenClassification over 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    1.11 GB
    xet
    Upload XLMRobertaForTokenClassification over 2 years ago
  • special_tokens_map.json
    280 Bytes
    Upload tokenizer over 2 years ago
  • tokenizer.json
    17.1 MB
    xet
    Upload tokenizer over 2 years ago
  • tokenizer_config.json
    609 Bytes
    Upload tokenizer over 2 years ago