Instructions to use AnonymousCS/populism_classifier_bsample_303 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_303 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_303")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_303") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_303", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3de91ef846100615cc0de0e44cf7af90eddb9965a8709bc471d5c5c8c16560a0
- Size of remote file:
- 5.43 kB
- SHA256:
- 63b4588fb110b53b7c24fb8d6bdc5062ee03cfc16f4183ed6846c40f625dd1fd
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