Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use christinacdl/RoBERTa-Clickbait-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christinacdl/RoBERTa-Clickbait-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="christinacdl/RoBERTa-Clickbait-Detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("christinacdl/RoBERTa-Clickbait-Detection") model = AutoModelForSequenceClassification.from_pretrained("christinacdl/RoBERTa-Clickbait-Detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d1d115b6bc4a978c5be2c2e01628d8391fdb74ec545d33ccfa03e7e69fe25ec
- Size of remote file:
- 1.42 GB
- SHA256:
- 3c7fcaf4f0b23233b2c0224363b78c99a81d665373626d64a328bbd845879a71
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