Instructions to use Mascariddu8/postText-TargetParagraphs_clickbait_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mascariddu8/postText-TargetParagraphs_clickbait_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mascariddu8/postText-TargetParagraphs_clickbait_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mascariddu8/postText-TargetParagraphs_clickbait_model") model = AutoModelForSequenceClassification.from_pretrained("Mascariddu8/postText-TargetParagraphs_clickbait_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7e892b4ddb62200d60317590100e0f4408ec289c4314a5a38269cab680ab23a
- Size of remote file:
- 512 MB
- SHA256:
- d33aac69bc55fd407fba2d88390c5bf51432729bcc1d01ae679ecc8dd4a747fa
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