Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use gabrielZang/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gabrielZang/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="gabrielZang/bert-finetuned-ner", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("gabrielZang/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("gabrielZang/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 367f6a8c566e5db00bc9c28d3ff45ec09212a510846892ba7bab869028a0f3ea
- Size of remote file:
- 431 MB
- SHA256:
- 0cde19c8a504ef6a3fa406a1fed6cf4924d74aedf46de5c9cb8f02dd93f01c45
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