Instructions to use AnonymousCS/populism_classifier_bsample_332 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_332 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_332")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_332") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_332", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd66f3000b2b73dcbe24d7535d5b56c6e2a46db92fdbfb5b94c85dcfe119121f
- Size of remote file:
- 1.33 GB
- SHA256:
- aa47200190a31c7a23d647c2eccfb9423f85dd5b16a39f8587409c4424d68a92
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