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--- |
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license: cc-by-4.0 |
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datasets: |
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- dell-research-harvard/newswire |
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language: |
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- en |
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pipeline_tag: text-classification |
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tags: |
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- distilroberta |
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- topic |
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- news |
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widget: |
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- text: "Diplomatic efforts to deal with the world’s two wars — the civil war in Spain and the undeclared Chinese - Japanese conflict — received sharp setbacks today." |
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- text: "WASHINGTON. AP. A decisive development appeared in the offing in the tug-of-war between the federal government and the states over the financing of relief." |
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- text: "A frantic bride called the Rochester Gas and Electric corporation to complain that her new refrigerator “freezes ice cubes too fast.”" |
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--- |
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# Fine-tuned DistilRoBERTa-base for detecting news on politics |
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# Model Description |
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This model is a finetuned RoBERTa-large, for classifying whether news articles are about politics. |
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# How to Use |
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```python |
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from transformers import pipeline |
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classifier = pipeline("sentiment-analysis", model="dell-research-harvard/topic-politics") |
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classifier("Kennedy wins election") |
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``` |
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# Contact |
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# Reference |
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