Instructions to use AnonymousCS/populism_classifier_bsample_320 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_320 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_320")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_320") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_320") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 380437fda44f9cc11b978aec27abde44377b1a13bf3161bf9a532427e386d419
- Size of remote file:
- 1.33 GB
- SHA256:
- 56fd93291ab5743318a8d23a1e94700b2699b2a268c199306af6e99504b8844b
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