Instructions to use AnonymousCS/populism_classifier_bsample_378 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_378 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_378")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_378") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_378", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70c0acfda2a43b0ccfc85b2636561ad6b8558c9b5c747a5c1b02cbf47b7191a0
- Size of remote file:
- 1.34 GB
- SHA256:
- fff49de89f36cbcb10d55804f75e849802ff76213e13f4303503abf9827c9c9a
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