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:
- f73786b1d49c8dc5e14c36ba3520e4801e7f61b5d9bf3e750847f0f18e405f86
- Size of remote file:
- 471 MB
- SHA256:
- 221cd7d670de7261f4d4498018d2a86b8cf4e625b8c398001a44809ff630707b
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