Instructions to use classla/bcms-bertic-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/bcms-bertic-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="classla/bcms-bertic-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("classla/bcms-bertic-ner") model = AutoModelForTokenClassification.from_pretrained("classla/bcms-bertic-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3df97a0437bbbd553cf972a76747d31193123fc0255cde00b512588f04b17673
- Size of remote file:
- 440 MB
- SHA256:
- b09133ea0ba4943404b062e04a89963eb9a7ccbd1983a69b9ed36818f4d84b3f
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