Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use vikram15/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikram15/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vikram15/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("vikram15/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("vikram15/bert-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48e7fcd8e3d6e698ed3b122df4ddf76d0458a6b0e3207628019fb5a05a19dce5
- Size of remote file:
- 3.38 kB
- SHA256:
- 716b572d11bdbbd61066cb8b550714c00ee5a3b67c181aafe596615ce6a10f45
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