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csocsci
/
xlm-roberta-large-binary-cs-iib

Feature Extraction
Transformers
PyTorch
Czech
xlm-roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use csocsci/xlm-roberta-large-binary-cs-iib with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use csocsci/xlm-roberta-large-binary-cs-iib with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="csocsci/xlm-roberta-large-binary-cs-iib")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("csocsci/xlm-roberta-large-binary-cs-iib")
    model = AutoModel.from_pretrained("csocsci/xlm-roberta-large-binary-cs-iib")
  • Notebooks
  • Google Colab
  • Kaggle
xlm-roberta-large-binary-cs-iib
2.26 GB
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  • 2 contributors
History: 7 commits
csocsci's picture
csocsci
Update README.md
41b0313 verified over 1 year ago
  • .gitattributes
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  • README.md
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  • config.json
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    2.24 GB
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  • sentencepiece.bpe.model
    5.07 MB
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  • special_tokens_map.json
    279 Bytes
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
    472 Bytes
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