Instructions to use AnonymousCS/populism_classifier_bsample_289 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_289 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_289")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_289") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_289", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ceb0fd4d648cec49d2cb81b22a62ba46aba871ac9d97196a2c08da9e9dc3e97c
- Size of remote file:
- 5.43 kB
- SHA256:
- 3c134850789685f6d9410d7b2002e58f2e39a914a2cb958640751c96a120be4f
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