Instructions to use AnonymousCS/populism_classifier_bsample_371 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_371 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_371")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_371") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_371", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa9ae5317b7647377aac9cfb96ee4ae2ac30c56f24c8d0cee0be72c32c52a41e
- Size of remote file:
- 1.34 GB
- SHA256:
- 063d1a2ce9a9c9056591cd5dcc2dc3951afe1aa9efccd28fb21d24a692fb8296
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