Instructions to use AnonymousCS/populism_classifier_bsample_350 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_350 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_350")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_350") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_350", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec7d40c7cb6ab2d850f1f8ad7276ce803b736f4a61b543607b19e2048d33402a
- Size of remote file:
- 438 MB
- SHA256:
- f3504bcc998ab836cf2afe53c6c99d00dc44aaa849c51fd59b39a95270d6f682
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