Instructions to use AnonymousCS/populism_classifier_bsample_347 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_347 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_347")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_347") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_347", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b686021850d1fd55aa057c88576e9b54e643269d772e28808e6df7a9705cacef
- Size of remote file:
- 438 MB
- SHA256:
- 45f577de62362d3ef323d0242f3d2325a90829ba639b52a1d177946910d11599
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