Instructions to use moctarsmal/bert-ner-chunks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moctarsmal/bert-ner-chunks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="moctarsmal/bert-ner-chunks")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("moctarsmal/bert-ner-chunks") model = AutoModelForTokenClassification.from_pretrained("moctarsmal/bert-ner-chunks", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66dc6d90d240ed93f4c9c558794ae9efee7f8c3f42d17c1710a2f8f09ec062db
- Size of remote file:
- 4.66 kB
- SHA256:
- 85d8d4177c5942bfafc39d4c43b3f5b1554e8c801b8088951e4c2d20f71de860
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