Instructions to use AnonymousCS/populism_classifier_bsample_392 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_392 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_392")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_392") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_392", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 762b0ca1193eed3260c468a2141e6aa3edd5ed8d6bc7d824eb254247a46b9e88
- Size of remote file:
- 5.43 kB
- SHA256:
- acf94c60942fcec8cfe2011ed96ad99c418ac05a1058d28d978f39caa4bbb02a
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