Instructions to use MutazYoune/Arabic-NER-PII_dialect-patterns_small-dialect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MutazYoune/Arabic-NER-PII_dialect-patterns_small-dialect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MutazYoune/Arabic-NER-PII_dialect-patterns_small-dialect")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MutazYoune/Arabic-NER-PII_dialect-patterns_small-dialect") model = AutoModelForTokenClassification.from_pretrained("MutazYoune/Arabic-NER-PII_dialect-patterns_small-dialect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0a0ef9ea59636b62f3314fddb36a40526885df155290d782f613d827789be80
- Size of remote file:
- 434 MB
- SHA256:
- e8df71311e36f74b918a24aeaaa3cd1eccca9b58d6f820dd98e0aa328c4fae3e
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