Instructions to use AnonymousCS/populism_classifier_bsample_353 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_353 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_353")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_353") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_353", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 524a40b44c94e1bd1eeac9e66e05c0907730af8b7fe1befccd96072def27e6a6
- Size of remote file:
- 438 MB
- SHA256:
- 936b7771c53afd9c4b90d54e49b067784983b23ca64fcae832e369fc2b7269ea
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