Instructions to use AnonymousCS/populism_classifier_391 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_391 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_391")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_391") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_391", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 566236e8825d280c3a35c484d04008ecbec0c3b153ad012d7fc4ac2635eb06eb
- Size of remote file:
- 5.43 kB
- SHA256:
- b9cece0c8f4b5f81fa3732d7d1d69a53ba2baf0d76112988b8fb2f3f73bc798b
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