Instructions to use Tirendaz/my_ner_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tirendaz/my_ner_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tirendaz/my_ner_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tirendaz/my_ner_model") model = AutoModelForTokenClassification.from_pretrained("Tirendaz/my_ner_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d12cdbe1f3feaf26dad694b23ca750553584e8e0aa13800afcbdd6b7505c5d18
- Size of remote file:
- 4.03 kB
- SHA256:
- fce326c05fb68fc757551d5a6f3bee32c2ddef122a69de2a5b301604d73f642f
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