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mopatik
/
PuoBERTa_MRP_version

Text Classification
Transformers
Safetensors
Tswana
roberta
offensive-language-detection
setswana
low-resource-nlp
digital-forensics
explainable-ai
rationale-learning
masked-rationale-prediction
puoberta
lime
s-lime
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use mopatik/PuoBERTa_MRP_version with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mopatik/PuoBERTa_MRP_version with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="mopatik/PuoBERTa_MRP_version")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("mopatik/PuoBERTa_MRP_version")
    model = AutoModelForSequenceClassification.from_pretrained("mopatik/PuoBERTa_MRP_version")
  • Notebooks
  • Google Colab
  • Kaggle
PuoBERTa_MRP_version
500 MB
Ctrl+K
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  • 1 contributor
History: 4 commits
mopatik's picture
mopatik
Update README.md
47d930e verified 3 days ago
  • .gitattributes
    1.52 kB
    initial commit 3 days ago
  • README.md
    14.8 kB
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  • config.json
    689 Bytes
    Upload 4 files 3 days ago
  • model.safetensors
    499 MB
    xet
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  • tokenizer.json
    1.29 MB
    Upload 4 files 3 days ago
  • tokenizer_config.json
    386 Bytes
    Upload 4 files 3 days ago