Token Classification
Transformers
PyTorch
TensorFlow
Arabic
English
bert
text-classification
BERT
sequence-tagger-model
Instructions to use ychenNLP/arabic-ner-ace with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ychenNLP/arabic-ner-ace with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ychenNLP/arabic-ner-ace")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ychenNLP/arabic-ner-ace") model = AutoModelForSequenceClassification.from_pretrained("ychenNLP/arabic-ner-ace", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd5393cbcb40b9c02058c8d5647dc6c07f2204d173a619d3c2f8f7927473e243
- Size of remote file:
- 498 MB
- SHA256:
- cb6893c16bc620c4e698e08dd0b47a114ec9cca96ca63c378ee114824ea7bbee
ยท
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