Instructions to use AnonymousCS/populism_classifier_bsample_136 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_136 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_136")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_136") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_136") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32d5b479324b7ce380f440b0edf3fabd5883c0adc2628566add71ec03fa24e89
- Size of remote file:
- 711 MB
- SHA256:
- 4a9e5ecfbe638cf882e36a0e9ca66a7d0777b12648ea95d336d2a5e36cfc122b
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