Instructions to use AnonymousCS/populism_classifier_bsample_363 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_363 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_363")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_363") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_363", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a28172a783c28e365274c1982404a372b6cc307d8b45f696433e333104e85617
- Size of remote file:
- 438 MB
- SHA256:
- 3bd6dbe68cef2b3b09674afcf28bf1ee1002a3e9a36fceafa7a03004fb55a3c2
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