Text Classification
Transformers
PyTorch
English
roberta
Tweet
Twitter
Clickbait
Spam
text-embeddings-inference
Instructions to use Stremie/roberta-base-clickbait with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Stremie/roberta-base-clickbait with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Stremie/roberta-base-clickbait")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Stremie/roberta-base-clickbait") model = AutoModelForSequenceClassification.from_pretrained("Stremie/roberta-base-clickbait") - Notebooks
- Google Colab
- Kaggle
This model classifies whether a tweet is clickbait or not. It has been trained using Webis-Clickbait-17 dataset. Input is composed of 'postText'. Achieved ~0.7 F1-score on test data.
In order to test this model, try a tweet on the right!
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