Instructions to use AnonymousCS/populism_classifier_bsample_149 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_149 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_149")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_149") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_149", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f7fb0a238862f627ec9291dd273d671d3da5b07a71c01b3ad7cc4be0a927153
- Size of remote file:
- 5.43 kB
- SHA256:
- 1c625cdad6009ef6597edad4cd2249dc3fa159a9626b2db4a22d28602953c665
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