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SEACrowd
/
mdeberta-v3_sea_translationese

Text Classification
Transformers
Safetensors
deberta-v2
translationese
classification
sea
southeast asia
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use SEACrowd/mdeberta-v3_sea_translationese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use SEACrowd/mdeberta-v3_sea_translationese with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="SEACrowd/mdeberta-v3_sea_translationese")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("SEACrowd/mdeberta-v3_sea_translationese")
    model = AutoModelForSequenceClassification.from_pretrained("SEACrowd/mdeberta-v3_sea_translationese")
  • Notebooks
  • Google Colab
  • Kaggle
mdeberta-v3_sea_translationese
1.14 GB
Ctrl+K
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  • 3 contributors
History: 9 commits
holylovenia's picture
holylovenia
Update README.md
877c97b verified almost 2 years ago
  • .gitattributes
    1.57 kB
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  • README.md
    6.92 kB
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  • added_tokens.json
    23 Bytes
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  • config.json
    1.04 kB
    Upload DebertaV2ForSequenceClassification about 2 years ago
  • model.safetensors
    1.12 GB
    xet
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  • special_tokens_map.json
    286 Bytes
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  • spm.model
    4.31 MB
    xet
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  • tokenizer.json
    16.3 MB
    xet
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  • tokenizer_config.json
    1.28 kB
    Upload tokenizer about 2 years ago