Instructions to use AnonymousCS/populism_classifier_bsample_320 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_320 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_320")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_320") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_320", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87a82a24166494d7cfb59849d7c631e801f33b67794146b62f874381fb4c64db
- Size of remote file:
- 5.43 kB
- SHA256:
- cfefe0c2684850050b21252491a29383bfd0fd4ad51eb7a9a12b4473004cbd5e
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