Instructions to use AnonymousCS/populism_classifier_bsample_385 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_385 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_385")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_385") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_385", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd40582d6044cecc7117b9a2950473eb033c382a102790062b1470214010318f
- Size of remote file:
- 5.43 kB
- SHA256:
- 473eaf6679428c0140fad4634bae51b8dae4940fb68c10c0823a451f0db813d5
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