Instructions to use spraxx/bert-base-cased-conll2003-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spraxx/bert-base-cased-conll2003-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="spraxx/bert-base-cased-conll2003-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("spraxx/bert-base-cased-conll2003-ner") model = AutoModelForTokenClassification.from_pretrained("spraxx/bert-base-cased-conll2003-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe5fe0f4789108879313fef6f6f4de2569a33bcec4de2d33b870e2aea2492066
- Size of remote file:
- 5.2 kB
- SHA256:
- 351c75c77591274a75bb5cbd9484e78abe13b3dd312349f7099f76b619360c12
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