Instructions to use AnonymousCS/populism_classifier_bsample_132 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_132 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_132")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_132") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_132", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52da9451ed53663b187eaf60eba43a4f095e2bc4cca8567798fe0b276e3915ad
- Size of remote file:
- 711 MB
- SHA256:
- da68e16e2558b90b7288a11188f17c8654aa3f726a4c072cd799f0b7ff1c6b11
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