Instructions to use AnonymousCS/populism_classifier_bsample_379 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_379 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_379")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_379") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_379", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2ddcfd770c2197b4e10c8a91a6d1b3a0d246a877789ccb0aae0cefc58c0c1da
- Size of remote file:
- 1.34 GB
- SHA256:
- c632b5036e5eab10c1b70aebcd89aa1a795a3d54a1ac001bd1c60bba1dc765f5
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