Instructions to use AnonymousCS/populism_classifier_bsample_176 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_176 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_176")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_176") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_176", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9aaf8be0c6392b3c5c9af7772d21ca4b212c7bc4bb21a7c939423d2d0268d5e7
- Size of remote file:
- 5.43 kB
- SHA256:
- be3ae79a56ed77baac8ad3f0dab19937dbf10c44318c8c8903623eedef90d923
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