Instructions to use AnonymousCS/populism_classifier_bsample_391 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_391 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_391")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_391") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_391", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb4714d6c02ffe0e7b93d30f2303024389b0c4b696a7b5b2c5f1ad825229470e
- Size of remote file:
- 2.3 GB
- SHA256:
- 7939f9ab720c84e6361306071019d71dcaa33037ecc2dab924394cc8d3318627
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