Instructions to use AnonymousCS/populism_classifier_bsample_387 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_387 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_387")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_387") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_387", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a09e105b4f3ac69f925ea65f53809603475d190761b6feb103a2399c6eb671c2
- Size of remote file:
- 1.34 GB
- SHA256:
- 26ee6bc17ddba9a320287f49fcc2d1b6db4fd0af14e800eb5edcf29d49a40110
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