Instructions to use Sami92/XLM-R-Large-Sensationalism-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sami92/XLM-R-Large-Sensationalism-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sami92/XLM-R-Large-Sensationalism-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sami92/XLM-R-Large-Sensationalism-Classifier") model = AutoModelForSequenceClassification.from_pretrained("Sami92/XLM-R-Large-Sensationalism-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9f8ea4a55c5028c2f35281e4db0ba5ab2e611c89330afe234477c21b8e265cb
- Size of remote file:
- 2.24 GB
- SHA256:
- efcfd2506fd3fdbf4359d021ce731e2ab251b8a61667162c06e0330274b49c63
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