Instructions to use AnonymousCS/populism_classifier_bsample_406 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_406 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_406")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_406") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_406", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c8eed02cca9b37e032edb54a3db257298e7452907036d3846d0d767177e8059
- Size of remote file:
- 2.3 GB
- SHA256:
- 7eb061f681e4aa9298606349d5fcced7be37fe98c16c7a1983cb9c1e7fbcd700
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