Instructions to use HooshvareLab/bert-fa-zwnj-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-fa-zwnj-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HooshvareLab/bert-fa-zwnj-base-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-fa-zwnj-base-ner") model = AutoModelForTokenClassification.from_pretrained("HooshvareLab/bert-fa-zwnj-base-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8df88696ff16f364366bd481a223bca6d20f2cae762ed13d1afe1567719c0162
- Size of remote file:
- 471 MB
- SHA256:
- 5d9e3bb2a80a63702f51e77146aba8c8df4c71258b695df29d6bd6b61ce8a723
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