Instructions to use terzimert/bert-finetuned-ner-balancedData_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use terzimert/bert-finetuned-ner-balancedData_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="terzimert/bert-finetuned-ner-balancedData_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("terzimert/bert-finetuned-ner-balancedData_v2") model = AutoModelForTokenClassification.from_pretrained("terzimert/bert-finetuned-ner-balancedData_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
pytorch_model.bin
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runs/Mar24_10-17-59_5e7d11ac7e73/1679653262.1482515/events.out.tfevents.1679653262.5e7d11ac7e73.891.1
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training_args.bin
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