Instructions to use dgramus/ner-best-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dgramus/ner-best-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dgramus/ner-best-model")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dgramus/ner-best-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37fa5df07ae8249a1b7e74d93d16660a53cd51c289b2f8fb18f5c8318b1c5bf7
- Size of remote file:
- 4.6 kB
- SHA256:
- 224898caa4b939a513aeca0355257699e682745ca1cf8522e639655aac95c842
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