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:
- eb18e7c990bb6beee471b63637449974fe582e7ec74e11070b92ff61d3074b6e
- Size of remote file:
- 711 MB
- SHA256:
- 326872d7c90db34f72998de36eaa6b604e1081523aeacd7612e7eb31a6d145ec
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