Instructions to use MutazYoune/Arabic-NER-PII_dialect-patterns-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-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-dialect")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MutazYoune/Arabic-NER-PII_dialect-patterns-dialect") model = AutoModelForTokenClassification.from_pretrained("MutazYoune/Arabic-NER-PII_dialect-patterns-dialect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ab5ef005145327261a10afd35d49595516784d59e7adfd766c02f02d4641e54
- Size of remote file:
- 434 MB
- SHA256:
- 678393d36ad34bb375a519c7a98d46ced904e9c7b93f17684cb1136be43675b2
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