Instructions to use HooshvareLab/bert-base-parsbert-ner-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-base-parsbert-ner-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HooshvareLab/bert-base-parsbert-ner-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-base-parsbert-ner-uncased") model = AutoModelForTokenClassification.from_pretrained("HooshvareLab/bert-base-parsbert-ner-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update test_results.txt
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test_results.txt
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eval_loss = 0.03034645883371703
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eval_precision = 0.9455721614989963
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eval_recall = 0.9571009257168661
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eval_f1 = 0.9513016157989228
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