Instructions to use AnonymousCS/populism_classifier_bsample_385 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_385 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_385")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_385") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_385", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ffcd5f22798cf9b7a664079a277a87ef5aff2e690e5b5146b30f38fc00fbdcf
- Size of remote file:
- 1.34 GB
- SHA256:
- 6119b182ade18d83d3ba7986ca0834190ea74105b0677fbdf8af78df9dc8e1d5
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