Instructions to use AnonymousCS/populism_classifier_bsample_293 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_293 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_293", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_293") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_293", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c6346939e8e882637fcd127a546811c0f3699fc7d3930ab2d777391f4f5f6af
- Size of remote file:
- 433 MB
- SHA256:
- a855d2e8be7854c21e00e355e98efbdbc591a9254686108d2f4cc4ca11bf7eca
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