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ICTuniverse
/
XLM-R-large-qa-one-shot-viwiki

Question Answering
Transformers
Safetensors
xlm-roberta
Model card Files Files and versions
xet
Community

Instructions to use ICTuniverse/XLM-R-large-qa-one-shot-viwiki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ICTuniverse/XLM-R-large-qa-one-shot-viwiki with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("question-answering", model="ICTuniverse/XLM-R-large-qa-one-shot-viwiki")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForQuestionAnswering
    
    tokenizer = AutoTokenizer.from_pretrained("ICTuniverse/XLM-R-large-qa-one-shot-viwiki")
    model = AutoModelForQuestionAnswering.from_pretrained("ICTuniverse/XLM-R-large-qa-one-shot-viwiki")
  • Notebooks
  • Google Colab
  • Kaggle
XLM-R-large-qa-one-shot-viwiki
2.26 GB
Ctrl+K
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  • 1 contributor
History: 3 commits
ICTuniverse's picture
ICTuniverse
Upload tokenizer
d3fc224 verified 8 months ago
  • .gitattributes
    1.57 kB
    Upload tokenizer 8 months ago
  • README.md
    5.17 kB
    Upload XLMRobertaForQuestionAnswering 8 months ago
  • config.json
    678 Bytes
    Upload XLMRobertaForQuestionAnswering 8 months ago
  • model.safetensors
    2.24 GB
    xet
    Upload XLMRobertaForQuestionAnswering 8 months ago
  • sentencepiece.bpe.model
    5.07 MB
    xet
    Upload tokenizer 8 months ago
  • special_tokens_map.json
    280 Bytes
    Upload tokenizer 8 months ago
  • tokenizer.json
    17.1 MB
    xet
    Upload tokenizer 8 months ago
  • tokenizer_config.json
    1.18 kB
    Upload tokenizer 8 months ago