Instructions to use AnonymousCS/populism_classifier_bsample_367 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_367 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_367")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_367") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_367") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 561e5bcc0c05294bce847f2f256781f6855a78cb7e76e728bac74851e141c276
- Size of remote file:
- 1.34 GB
- SHA256:
- aba40e883a23938ba4c8c1ad08b65c9a38ec45f64d58bb408aa48f96cf5b6ff4
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