Instructions to use saroyehun/CAP_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saroyehun/CAP_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="saroyehun/CAP_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("saroyehun/CAP_classifier") model = AutoModelForSequenceClassification.from_pretrained("saroyehun/CAP_classifier") - Notebooks
- Google Colab
- Kaggle
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README.md
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This is a
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This model was trained specifically for additional analyses presented in this [paper](https://doi.org/10.48550/arXiv.2405.07323).
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This is a transformers model trained on the U.S. Comparative Agendas Project (CAP) dataset, annotated with a top-level taxonomy covering 20 policy areas, as well as an "Others" category for non-policy-related text. The model is designed to identify policy and non-policy issues in political discourse.
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This model was trained specifically for additional analyses presented in this [paper](https://doi.org/10.48550/arXiv.2405.07323).
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