Instructions to use AnonymousCS/populism_classifier_bsample_393 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_393 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_393")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_393") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_393", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23abbe03e6cf3a7766453ae1e1c46117af3073c99ad9cc00ce3627403762f3c9
- Size of remote file:
- 2.3 GB
- SHA256:
- cf30d0fcfd81817a11f39b8ec2bb9de793238064aa1bebdda4696f1ff85f0492
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