Instructions to use AnonymousCS/populism_classifier_bsample_389 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_389 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_389")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_389") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_389", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2d59a52e0740cfc39d26998ee4b78cff09273f729941599c8ce6ee5cea8564e
- Size of remote file:
- 5.43 kB
- SHA256:
- 5b9e0ca22e44d9dc18d09246f22bb7b91aa7bb63fb382dddec21b8f155414291
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