Instructions to use AnonymousCS/populism_classifier_bsample_332 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_332 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_332")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_332") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_332", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 116f8a221a0a62917917ec0837aa890f5b25a5d5da491242c86f521f9ca509d7
- Size of remote file:
- 5.43 kB
- SHA256:
- 87456b47e64d7ee4b1dbed36c82da11e96f6768550627716b57e285c8934e99d
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