Instructions to use Vasanth/bert-ner-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vasanth/bert-ner-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Vasanth/bert-ner-custom")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Vasanth/bert-ner-custom") model = AutoModelForTokenClassification.from_pretrained("Vasanth/bert-ner-custom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac9ca4b8e57c2a5884b5de644d1b5ef839dcadddf805de38d0787a2e30a17cfd
- Size of remote file:
- 431 MB
- SHA256:
- 26068a5296eafb3bbad64d1201871fb8bdcc843843b65b7d6885a140e183d36b
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