Instructions to use AnonymousCS/populism_classifier_bsample_321 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_321 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_321")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_321") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_321", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c43ad1d94796126816da0b3659509d701037a6858cb1b0e95a7c150e3ad26c90
- Size of remote file:
- 5.43 kB
- SHA256:
- 088b9d39d8e2255c850303c6f91056ba54fbb321a63108d5a837898dc46b4d02
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