Instructions to use AnonymousCS/populism_classifier_bsample_016 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_016 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_016")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_016") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_016", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a454639e29984e4fe4d66ae3267a1e359041617cce016791f246794ac88cad69
- Size of remote file:
- 711 MB
- SHA256:
- b812c15ea2aa925968ab13f2caf3cbf135041afdf1ce43856abb1ed040dc07ba
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