Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Gpaiva/NERDE-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gpaiva/NERDE-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Gpaiva/NERDE-base", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Gpaiva/NERDE-base") model = AutoModelForTokenClassification.from_pretrained("Gpaiva/NERDE-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
fix typo
Browse files- config.json +1 -1
config.json
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"0": "O",
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"1": "B-ORG",
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"2": "I-ORG",
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"3": "B-
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"4": "I-PER",
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"5": "B-TEMPO",
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"6": "I-TEMPO",
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"0": "O",
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"1": "B-ORG",
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"2": "I-ORG",
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"3": "B-PER",
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"4": "I-PER",
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"5": "B-TEMPO",
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"6": "I-TEMPO",
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