Instructions to use caush/Clickbait5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caush/Clickbait5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="caush/Clickbait5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("caush/Clickbait5") model = AutoModelForSequenceClassification.from_pretrained("caush/Clickbait5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 243bc59b495c5b0d2b84a286f7eb1067350dcf1320e78e136fcc8ef79bfc8f8c
- Size of remote file:
- 2.99 kB
- SHA256:
- 998d65df5c44c22333ca3ad1d94a6edd4da42fbd79404c5e63e7a406a4a8a347
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