Text Classification
Transformers
Safetensors
English
roberta
clickbait
clickbait-detection
moderation
content-moderation
text-embeddings-inference
Instructions to use ENTUM-AI/roberta-clickbait-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ENTUM-AI/roberta-clickbait-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ENTUM-AI/roberta-clickbait-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ENTUM-AI/roberta-clickbait-classifier") model = AutoModelForSequenceClassification.from_pretrained("ENTUM-AI/roberta-clickbait-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa01392553052b71215571c6573ffbda256b7683c4bf4e5228510059276693c8
- Size of remote file:
- 499 MB
- SHA256:
- 217e1e1259a57f18f9e5558f0a064550c55aac544a622e4990660b6d1f6bf91f
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