Instructions to use AnonymousCS/populism_classifier_332 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_332 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_332")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_332") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_332", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8d9bba662b8b639532198f90077ecd4620d1e7bb8447c37112668ed9b968bb7
- Size of remote file:
- 5.43 kB
- SHA256:
- d68bda7fbcf580fdc975577cbfbf01251ab1be35d8b37838d21a1eec51ea9c58
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