Instructions to use AnonymousCS/populism_classifier_bsample_337 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_337 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_337")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_337") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_337", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50cfd888eea374fa9d5cb6749b729301f88d36fa1a8a850ea7091da7162fbec5
- Size of remote file:
- 5.43 kB
- SHA256:
- 8087deb1ba3a6e318ec7333eeea69d668a3603b2a2eaabb5fc961fbc513402e9
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