Instructions to use AnonymousCS/populism_classifier_bsample_133 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_133 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_133")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_133") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_133", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99be9784439901cf016c2d20de961ef1e6c940ead884c8ae40609fc29d73f762
- Size of remote file:
- 5.43 kB
- SHA256:
- c7122a068818fa05c968bbd72a28496a4402fcc91e9b4fa2cf4b6fe377d5785f
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