Instructions to use AnonymousCS/populism_classifier_bsample_153 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_153 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_153")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_153") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_153", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c7195727f5dbdc9d8243c655a23d76344fe2d2cb6ee797e71f642a47d0cd1e6
- Size of remote file:
- 711 MB
- SHA256:
- 843c8878bd82b3d63817431f725f4f4c2fdb6455e18fa960671c6f1b298c8174
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