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--- |
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license: gpl-2.0 |
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language: |
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- en |
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--- |
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# Fake News Recognition |
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<!-- Provide a quick summary of what the model is/does. --> |
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This model is fine-tuned Roberta model 'jy46604790/Fake-News-Bert-Detect' (https://huggingface.co/jy46604790/Fake-News-Bert-Detect). |
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This model is trained by 8 000 news articles from https://euvsdisinfo.eu/ portal. |
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It can give result by simply entering the text of the news less than 512 words(the excess will be truncated automatically). |
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Labels: |
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* 0: Fake news |
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* 1: Real news |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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### Download The Model |
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``` |
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from transformers import pipeline |
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MODEL = "winterForestStump/Roberta-fake-news-detector" |
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clf = pipeline("text-classification", model=MODEL, tokenizer=MODEL) |
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``` |
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### Feed Data |
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``` |
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text = "From the very beginning, the EU has been extremely non-transparent. The deployment of the European Union presence in Armenia was carried out forcefully, under serious pressure from Brussels" |
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``` |
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### Result |
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``` |
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result = clf(text) |
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result |
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``` |
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### Output |
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``` |
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[{'label': 'FAKE', 'score': 0.9999946355819702}] |
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``` |
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About the data source EUVSDISINFO.eu: |
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Using data analysis and media monitoring services in multiple languages, EUvsDisinfo identifies, compiles, and exposes disinformation cases originating in pro-Kremlin outlets. These cases (and their disproofs) are collected in the EUvsDisinfo database – the only searchable, open-source repository of its kind. The database is updated every week. |
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