koliskos/fake_news
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How to use koliskos/fine_tuned_fake_news_classifier with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="koliskos/fine_tuned_fake_news_classifier") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("koliskos/fine_tuned_fake_news_classifier")
model = AutoModelForSequenceClassification.from_pretrained("koliskos/fine_tuned_fake_news_classifier")Model is used to detect whether a news story is fake or legitimate.
Developed by: koliskos
Model type: Text Classification
Language(s) (NLP): English
License: mit
Finetuned from model: DistilBERT
Repository: koliskos/fine_tuned_fake_news_classifier
This model is meant to classify news articles as real or fake.
This model could potentially assume "fake" to be the default prediction for news stories that contain names that are seen heavily within fake news articles, ex: a news story about someone named Hillary may be labeled fake even if it is real because the name Hillary is heavily grounded within the context of Hillary Clinton.
spkolisko "at" wellesley.edu