Instructions to use onionLad/ner-tutorial-2024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use onionLad/ner-tutorial-2024 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="onionLad/ner-tutorial-2024")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("onionLad/ner-tutorial-2024") model = AutoModelForTokenClassification.from_pretrained("onionLad/ner-tutorial-2024", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f792b897080d81660137742eac70b203d8d52cbff4bbe951483210ee669d18c2
- Size of remote file:
- 4.98 kB
- SHA256:
- a40bab6c2da0429b4f4220bb6e146621e5f7e12365bdfabd1f64abf0e7f1c831
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