Instructions to use Gerwin/bert-for-pac with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gerwin/bert-for-pac with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gerwin/bert-for-pac")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gerwin/bert-for-pac") model = AutoModelForSequenceClassification.from_pretrained("Gerwin/bert-for-pac", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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#### Basic Information
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This model is fine-tuned on BERTje (https://github.com/wietsedv/bertje) for recognizing passive and active voice in Dutch sentences.
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- Accuracy: 0.983
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- F1: 0.983
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- Loss: 0.032
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- Precision: 0.967
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- Recall: 1.0
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This is the first release, have fun with it!
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An example on how to use it will come soon. Contact me at gerwindekruijf@gmail.com for further questions.
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#### Basic Information
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This model is fine-tuned on BERTje (https://github.com/wietsedv/bertje) for recognizing passive and active voice in Dutch sentences.
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Current release: Version 1.2
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Contact me at gerwindekruijf@gmail.com for further questions.
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Gerwin
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