Instructions to use caush/Clickbait3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caush/Clickbait3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="caush/Clickbait3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("caush/Clickbait3") model = AutoModelForSequenceClassification.from_pretrained("caush/Clickbait3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49a7c7ecd18eb2ea9eb7fc763820f76479885ebadc63bccf9ec38aaabb6e8ea9
- Size of remote file:
- 471 MB
- SHA256:
- 4f9b0140e2b4b17ba0280ed44814a0fd52ddd881461a935f02ffef32743b1880
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