Instructions to use cardiffnlp/pcl_robertabase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/pcl_robertabase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/pcl_robertabase")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/pcl_robertabase") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/pcl_robertabase") - Notebooks
- Google Colab
- Kaggle
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README.md
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This is the PCL detection model built on roBERTa-base.
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- Git Repo: [Don't Patronize Me! official repository](https://github.com/Perez-AlmendrosC/dontpatronizeme)
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- Dataset: [
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<b>Labels</b>:
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0 -> Negative;
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This is the PCL detection model built on roBERTa-base.
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- Git Repo: [Don't Patronize Me! official repository](https://github.com/Perez-AlmendrosC/dontpatronizeme)
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- Dataset: This model has been finetuned with the [Don't Patronize Me! dataset, available here](https://huggingface.co/datasets/carlaperez/dontpatronizeme_pcl)
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<b>Labels</b>:
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0 -> Negative;
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