Instructions to use AnonymousCS/populism_classifier_bsample_330 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_330 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_330")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_330") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_330", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a50d4af40d6123710a84a2f6304bd41ffdd95aa8bb572898959b66e865abe241
- Size of remote file:
- 1.33 GB
- SHA256:
- e6441f7beaa7941b981930e853f2555d2c14ee4398ced6177d25650cfb5736ac
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