Instructions to use AnonymousCS/populism_classifier_bsample_300 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_300 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_300")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_300") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_300", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b2a2fb6269a13add321eae3631376f99ea4d67926cad0748e8e2831f0836801
- Size of remote file:
- 5.43 kB
- SHA256:
- 88ac3941d9024d0d73ca97485f3b80a39702719fc7bea1340bded4b35c03239d
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