Instructions to use AnonymousCS/populism_classifier_bsample_368 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_368 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_368")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_368") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_368", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00d5df3e260f100eba67b2a59857b60336f96b2332702ced9842b162e4a53de4
- Size of remote file:
- 5.43 kB
- SHA256:
- 3259cffe4ceb94efa56392274994733ae9713ae08f61f19f89bf6a6c2a63ed73
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