Instructions to use andi611/bert-base-cased-ner-conll2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andi611/bert-base-cased-ner-conll2003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="andi611/bert-base-cased-ner-conll2003", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("andi611/bert-base-cased-ner-conll2003") model = AutoModelForTokenClassification.from_pretrained("andi611/bert-base-cased-ner-conll2003", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#3
by librarian-bot - opened
README.md
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name: Accuracy
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type: accuracy
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value: 0.9860628716077
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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name: Accuracy
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type: accuracy
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value: 0.9860628716077
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base_model: bert-base-cased
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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