Instructions to use AnonymousCS/populism_classifier_bsample_182 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_182 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_182")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_182") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_182", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7d0c6f3668a303bb306567e3645b6c979082d7f1083a75748d672553fd6c7cc
- Size of remote file:
- 5.43 kB
- SHA256:
- e3361335e54a9df4ada726e1c5d9d334a1e527119198682756f656fb1395f247
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