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:
- e7ea21b08d2b2b29cc4ba9e11afdba9b01cc791251d91994aea2812c1317697b
- Size of remote file:
- 471 MB
- SHA256:
- da2b9be3fff08c6c21e4cc32837631077768593523e55624196c14ba706c940a
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