Instructions to use AnonymousCS/populism_classifier_bsample_384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_384")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_384") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8080b72ff0b4539ea67a3b5f644e31cfda91a6356eff1de1e096c0b16a4b1304
- Size of remote file:
- 5.43 kB
- SHA256:
- 8b9d427228ecb6b3ed513a5f52b04102cc5d8d899ba09c90dfb764f771abaaca
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