Instructions to use Eraly-ml/KazBERT-NERD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eraly-ml/KazBERT-NERD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Eraly-ml/KazBERT-NERD")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Eraly-ml/KazBERT-NERD") model = AutoModelForTokenClassification.from_pretrained("Eraly-ml/KazBERT-NERD") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ab898230b0ac643670c053c73bd849d61061c52a6935256db57c42390a550a9
- Size of remote file:
- 440 MB
- SHA256:
- 76a968c83a676675aa78267c303f23f2e1739ae40c85ca88a970aedb606a0d8e
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