Fake News Recognition
This model is fine-tuned Roberta model 'jy46604790/Fake-News-Bert-Detect' (https://huggingface.co/jy46604790/Fake-News-Bert-Detect). This model is trained by 8 000 news articles from https://euvsdisinfo.eu/ portal. It can give result by simply entering the text of the news less than 512 words(the excess will be truncated automatically).
Labels:
- 0: Fake news
- 1: Real news
How to Get Started with the Model
Use the code below to get started with the model.
Download The Model
from transformers import pipeline
MODEL = "winterForestStump/Roberta-fake-news-detector"
clf = pipeline("text-classification", model=MODEL, tokenizer=MODEL)
Feed Data
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"
Result
result = clf(text)
result
Output
[{'label': 'FAKE', 'score': 0.9999946355819702}]
About the data source EUVSDISINFO.eu: 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.