Instructions to use AnonymousCS/populism_classifier_bsample_397 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_397 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_397", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_397") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_397", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac749ac58c5fd6da523e60285faa3b00b5c963bc0f0c9d9d337e1d8f0b200e6e
- Size of remote file:
- 2.3 GB
- SHA256:
- 87165429017613a162b7a8a4e1abd42bc652aa8a42a933517fd93e601f3dddd3
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