Instructions to use AnonymousCS/populism_classifier_bsample_148 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_148 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_148")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_148") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_148", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 872307bc33ba27b87f0de98bc2364c05f3b03a44932d34a22ca411df259253a7
- Size of remote file:
- 711 MB
- SHA256:
- 7df81ff5d1df498a17e534e79b10065de9662a33c5c3dfe2398e40b3a790ef71
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