Instructions to use MutazYoune/bert-base-arabic-camelbert-mix-ner-patterns with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MutazYoune/bert-base-arabic-camelbert-mix-ner-patterns with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MutazYoune/bert-base-arabic-camelbert-mix-ner-patterns")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MutazYoune/bert-base-arabic-camelbert-mix-ner-patterns") model = AutoModelForTokenClassification.from_pretrained("MutazYoune/bert-base-arabic-camelbert-mix-ner-patterns", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from MutazYoune/bert-base-arabic-camelbert-mix-ner-patterns: direct link, hf CLI and curl.
- Browser
- Download file 776 kB
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https://huggingface.co/MutazYoune/bert-base-arabic-camelbert-mix-ner-patterns/resolve/main/tokenizer.json
- Command line
-
hf download hf://MutazYoune/bert-base-arabic-camelbert-mix-ner-patterns/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/MutazYoune/bert-base-arabic-camelbert-mix-ner-patterns/resolve/main/tokenizer.json
776 kB
File too large to display, you can check the raw version instead.