Instructions to use AnonymousCS/populism_classifier_bsample_321 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_321 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_321")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_321") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_321") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f41dd63dcb93b843dab23e2cee97f089fb6c5588f906393ca054a1c7e2b4afd
- Size of remote file:
- 1.33 GB
- SHA256:
- 668a10aed4af4aa06dd32425cbbbee43aac43d5059c9c092bdf9c222a22e4f85
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