Instructions to use AnonymousCS/populism_classifier_bsample_368 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_368 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_368")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_368") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_368", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e4ee3a9eb6dba07dc37cdc3a1ca84aec6fcfc20713391eb580aff8cd3ac2ecf
- Size of remote file:
- 1.34 GB
- SHA256:
- 7ae6540e45d0920a68380e3d6b61a09da6622405cd6e597512b5a8b4eb1c0d77
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