Instructions to use jamie613/custom_BERT_NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jamie613/custom_BERT_NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jamie613/custom_BERT_NER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jamie613/custom_BERT_NER") model = AutoModelForTokenClassification.from_pretrained("jamie613/custom_BERT_NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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dataset=155, epochs=50, batch_size=1, early_stopping=eval_f1
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dataset=155, epochs=50, batch_size=1, early_stopping=eval_precision
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dataset=155, epochs=50, batch_size=1, early_stopping=eval_loss
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Training in progress, epoch 1
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