Instructions to use AnonymousCS/populism_classifier_bsample_003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_003")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_003") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_003", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e2d1c9ea81fa139cb6a8f7e1ff0248e2d4e18fb90503394c27619d3aae16873
- Size of remote file:
- 711 MB
- SHA256:
- 4c1ac60bfc5b2d22d8ffe55fa195f3bb96ed13906f327eb86169264cf2b89b00
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