Instructions to use AnonymousCS/populism_classifier_290 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_290 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_290")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_290") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_290", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3edb758f4e9de0a60f95cad5586d8f6f6d3d63d07a4f6c3b5416cadb9ef4fdcc
- Size of remote file:
- 5.43 kB
- SHA256:
- 8f8df2c5df85674ad4086603d2c6d2419467ea0808eee9b4ed1ad8c19346f96f
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