Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use sdinger/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdinger/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sdinger/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sdinger/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("sdinger/bert-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9d9c4e39a630e7f8ec04171a7ea9adbf335f0b7b8aa5de4143de6e8dfb93ec9
- Size of remote file:
- 3.96 kB
- SHA256:
- 209dca37b738e313bc35e1a47f5b4a9c520720051c9fb55e0c201d787baadd80
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