Instructions to use mpalaval/bert-ner-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/bert-ner-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mpalaval/bert-ner-1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mpalaval/bert-ner-1") model = AutoModelForTokenClassification.from_pretrained("mpalaval/bert-ner-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5add424b86e6e7e5ee96a5f9bfd95f7b81a392355cf86a53340c8ebcbfe04d1c
- Size of remote file:
- 4.54 kB
- SHA256:
- 19a6c1d9a1d18887ab2c7e0936d75b8f77aa9198d9544b1679b55459512c810f
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