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:
- 7eb0e297a8a9c8cfe6ca3b8e05452600c4d896559480ec070d46d0b3403d7300
- Size of remote file:
- 5.43 kB
- SHA256:
- 77c480ccb757dba75510f3f527a05d50fa176640a49a177ebc8aee70affe07c8
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