Instructions to use AnonymousCS/populism_classifier_bsample_378 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_378 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_378")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_378") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_378", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cc65ecb72e2899ed30ee44043114a0281e051a9e9947e74bd35ecb572d57662
- Size of remote file:
- 5.43 kB
- SHA256:
- aabc56e4d0537d82abe584528cabdbe2e989a55d5a362564abfe005901afdcc1
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