Instructions to use HooshvareLab/bert-fa-base-uncased-ner-arman with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-fa-base-uncased-ner-arman with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HooshvareLab/bert-fa-base-uncased-ner-arman")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-fa-base-uncased-ner-arman") model = AutoModelForTokenClassification.from_pretrained("HooshvareLab/bert-fa-base-uncased-ner-arman", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5826204db90d4782bf0434e36df07afe92947eadf0eec707b68728749369d06e
- Size of remote file:
- 652 MB
- SHA256:
- 8454d8f5754a534d54969c16a915775798977eada532300f046549143060e7c6
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