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:
- a3e0f054380758791f82676eff087ba21a6ea41203455b8cdf19c69482d189e8
- Size of remote file:
- 5.43 kB
- SHA256:
- 733fe67653c17b8e1ece8cad904d2259eaabaed9b1705f72dfd7e14de05bedbd
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