Instructions to use universalner/uner_qaf_ara with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalner/uner_qaf_ara with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="universalner/uner_qaf_ara")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("universalner/uner_qaf_ara") model = AutoModelForTokenClassification.from_pretrained("universalner/uner_qaf_ara") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e1452cac93ad200c0edbfc8d41001719a7ea4404591807839d329be2b8e0070
- Size of remote file:
- 2.24 GB
- SHA256:
- 9a6857e4741c0ba5b72dd6efb4215033b3f941d9b39d44c06a73e6d22e1d7327
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