Instructions to use AnonymousCS/populism_classifier_bsample_175 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_175 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_175")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_175") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_175", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bee6fd7e626327207a4e6f42c14e292b8f8bed7902975cf21a135da2b3c000ba
- Size of remote file:
- 5.43 kB
- SHA256:
- 7aaf4f9af0962115e99f82a4dc3887630747460060eac477b27e6d5f25a96013
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