Instructions to use AnonymousCS/populism_classifier_bsample_303 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_303 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_303")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_303") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_303", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9406c020349a9f39b73b26b04aac3e562d51b28b0de420fb40ee803758d563b
- Size of remote file:
- 433 MB
- SHA256:
- 135831046ca9e0fa411afefc1ac872c79fd5b1302b5c5338cb9f9a286c62662c
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