Token Classification
Transformers
PyTorch
TensorFlow
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use huggingface-course/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingface-course/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="huggingface-course/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("huggingface-course/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("huggingface-course/bert-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#6
by librarian-bot - opened
README.md
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@@ -9,6 +9,7 @@ metrics:
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- recall
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- f1
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- accuracy
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model-index:
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- name: test-bert-finetuned-ner
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results:
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- recall
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- f1
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- accuracy
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base_model: bert-base-cased
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model-index:
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- name: test-bert-finetuned-ner
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results:
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