Instructions to use AnonymousCS/populism_classifier_bsample_375 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_375 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_375")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_375") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_375", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a2b6e7b6844aa0386a205b075d60f4d728fa84e85ee5c7b9363a345eb60b401
- Size of remote file:
- 1.34 GB
- SHA256:
- 3899f03d03650e2eefd61abfa576157cc32f45b3f4b669b6383565a9ab42733b
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