Instructions to use AnonymousCS/populism_classifier_bsample_370 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_370 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_370")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_370") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_370", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a46f2c8724a628fcc76fa5d526333af248032e47c3fa0af4e198ad49978d5c6
- Size of remote file:
- 1.34 GB
- SHA256:
- 8e486bbcc230d5550154f455d88a3d07436a404babb403d4dadd015e2b3b699f
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