Instructions to use christinacdl/clickbait_binary_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christinacdl/clickbait_binary_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="christinacdl/clickbait_binary_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("christinacdl/clickbait_binary_detection") model = AutoModelForSequenceClassification.from_pretrained("christinacdl/clickbait_binary_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a86108ba1f5a9c67b61bf1d24f03bb2970a6e4575bfb812c2820ef6e34e16b1f
- Size of remote file:
- 3.64 kB
- SHA256:
- dcf76d4261cace24bf314c4b3825a0560877168ea9a615c5a13c8a472810b813
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