Instructions to use Mascariddu8/postText_clickbait_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mascariddu8/postText_clickbait_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mascariddu8/postText_clickbait_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mascariddu8/postText_clickbait_model") model = AutoModelForSequenceClassification.from_pretrained("Mascariddu8/postText_clickbait_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 463b4c90b0d0794b595b6d4c112cc613d1dd306e7bf846b859172ca30fe3be79
- Size of remote file:
- 512 MB
- SHA256:
- 20c4b64ec16d9ec2dfadc32e32f587d94ba39a0336c38f8a5317fba37b4afb23
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