Instructions to use AnonymousCS/populism_classifier_bsample_001 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_001 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_001")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_001") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_001", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe1ee000a2274de3f69fa274b94c150bf5c4cee3f9badf6bd98f13a85c7ec339
- Size of remote file:
- 711 MB
- SHA256:
- ee6de060f368e042388132633ee10f5579d2d6f0ed08b9ada1b166eed3a4922b
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