Instructions to use AnonymousCS/populism_classifier_bsample_315 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_315 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_315")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_315") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_315", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60dc80d1b0dfecac5d72fa6a0aa9f8ff7d580eacb884e4d1497afd9546d6bab1
- Size of remote file:
- 1.33 GB
- SHA256:
- e8d44d28893323dcf1caf9a9b6ef28f34398ec6f2bbff6ae8cd89f47c91c2b26
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