Instructions to use AnonymousCS/populism_classifier_387 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_387 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_387")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_387") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_387", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed171cc2ed8e5ea8a0f55d1095af6b0b0f86b82becf2b26ed76df4027342798a
- Size of remote file:
- 5.43 kB
- SHA256:
- 4e5083575e4c8d3f62a5f29924e28e34a803bb31252a73cde209f115aff4a1f4
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