Instructions to use AnonymousCS/populism_classifier_bsample_288 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_288 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_288")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_288") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_288", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2fcf309039facc0fc9d4bb2f3c1444d446cee7313fa11ea5bebd0446650f4c4
- Size of remote file:
- 5.43 kB
- SHA256:
- 65e44c4a73a26c87bb6e563be6b140e705515005735b67ba9ab5253d36bd1560
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