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:
- 1523a135d0b4e9fd8987bd7b5caa7758d8b04aec768d79aa2fc9faae39b8cf4f
- Size of remote file:
- 735 MB
- SHA256:
- 641142d4ecf4b9587beb1148006fc6f89c9021913f5a20d1c5805962ee06d155
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