Instructions to use AnonymousCS/populism_classifier_bsample_333 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_333 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_333")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_333") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_333", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6b69710d419bbc6b769c9cf3a47a157617e854f0ff5bfb3d24aabaa8070a85f
- Size of remote file:
- 1.33 GB
- SHA256:
- 738ba824e6928cf0b285a99be19335569704628a453e61b94c2eea66858a4313
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