Instructions to use AnonymousCS/populism_classifier_bsample_136 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_136 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_136")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_136") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_136", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c6df772eea0fd2c902b3a1ca4a0c9b155cde404b590f9f3e4b1e6087d8ec83a
- Size of remote file:
- 5.43 kB
- SHA256:
- 52241fb28234ff672aaeede4a731b57949b49ba20dd5a70814cb5933c37c2441
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