Instructions to use Mascariddu8/TargetParagraphs_clickbait_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mascariddu8/TargetParagraphs_clickbait_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mascariddu8/TargetParagraphs_clickbait_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mascariddu8/TargetParagraphs_clickbait_model") model = AutoModelForSequenceClassification.from_pretrained("Mascariddu8/TargetParagraphs_clickbait_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d2098534b347a6bb75e6bcfa2f7cf8f90a32de86146544e43ef9991235672d9
- Size of remote file:
- 512 MB
- SHA256:
- 756d01b11d8351ada35799214577bd08e1d4dca11ba5cf8966d8a1f9c3751220
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