Instructions to use AnonymousCS/populism_classifier_bsample_381 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_381 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_381")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_381") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_381", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 876b44428f976366e76a3ff873bab9bb263533f8b536c3a92ec93abe33c1cbb3
- Size of remote file:
- 1.34 GB
- SHA256:
- f6feae9884c55a3edc5d4d67624756a848d6a8cec2747dc32890230cf8185493
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