Instructions to use AnonymousCS/populism_classifier_bsample_393 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_393 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_393")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_393") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_393", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6164e092c584810cc03cda93f84b36a16080e12898c38e90bc729cb0295f89de
- Size of remote file:
- 5.43 kB
- SHA256:
- b2631875c2aa54ae644158b4be30b0c50c7af9e69c17e7764dc40900906dde42
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