Zero-Shot Classification
Transformers
ONNX
Safetensors
English
roberta
text-classification
nli
compliance
popia
south-africa
privacy
legal
quantized
cpu
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
Ctrl+K
docs: polish model card — link dataset, add limitations, raw ONNX snippet, label-index callout
3074d19 verified