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labrat-aiko
/
nli-popia-v1

Zero-Shot Classification
Transformers
ONNX
Safetensors
English
roberta
text-classification
nli
compliance
popia
south-africa
privacy
legal
quantized
cpu
Model card Files Files and versions
xet
Community

Instructions to use labrat-aiko/nli-popia-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use labrat-aiko/nli-popia-v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-classification", model="labrat-aiko/nli-popia-v1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("labrat-aiko/nli-popia-v1")
    model = AutoModelForSequenceClassification.from_pretrained("labrat-aiko/nli-popia-v1", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
nli-popia-v1
667 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
labrat-aiko's picture
labrat-aiko
docs: polish model card — link dataset, add limitations, raw ONNX snippet, label-index callout
3074d19 verified 4 months ago
  • onnx
    Initial upload: nli-popia-v1 (POPIA F1 0.813, +0.296 vs base) 4 months ago
  • pytorch
    Initial upload: nli-popia-v1 (POPIA F1 0.813, +0.296 vs base) 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • README.md
    8.09 kB
    docs: polish model card — link dataset, add limitations, raw ONNX snippet, label-index callout 4 months ago
  • config.json
    900 Bytes
    Initial upload: nli-popia-v1 (POPIA F1 0.813, +0.296 vs base) 4 months ago
  • eval.jsonl
    55 kB
    Initial upload: nli-popia-v1 (POPIA F1 0.813, +0.296 vs base) 4 months ago
  • tokenizer.json
    3.56 MB
    Initial upload: nli-popia-v1 (POPIA F1 0.813, +0.296 vs base) 4 months ago