Instructions to use AnonymousCS/populism_classifier_bsample_149 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_149 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_149")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_149") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_149", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cba6efc6d0e10f46d8e4f5d54df894285d918e25a49e908bd0b9f95b51d59793
- Size of remote file:
- 711 MB
- SHA256:
- 9598ba1defa2688fae19009abe3015b58e6eb944e7093c7a6b6a47d74cc7edc7
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