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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1618114f9c1605935c3fbd384e2c2cb9e214a4edc099f4bc694d568890304813
- Size of remote file:
- 496 MB
- SHA256:
- c4ac9cf454cd16e5cb43698cd1c6e7d0cc101a2c6bd8098cb8a73ce2ab102ad9
ยท
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