Text Classification
Transformers
PyTorch
Safetensors
Enawené-Nawé
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use Norah-K/PDPL_CAMeLBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Norah-K/PDPL_CAMeLBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Norah-K/PDPL_CAMeLBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Norah-K/PDPL_CAMeLBERT") model = AutoModelForSequenceClassification.from_pretrained("Norah-K/PDPL_CAMeLBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87f89890d7392ee5c6e5bf82b10f7ca8c31bd648fb36072a1226ddb3728e5636
- Size of remote file:
- 776 kB
- SHA256:
- 6dc8eda48177e61422409b994fc4d9e5bed69e24855ced2d7f1e888d28613618
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