Instructions to use AnonymousCS/populism_classifier_bsample_006 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_006 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_006")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_006") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_006", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e693417da73d9b1dbad6bf7548043bde98469078247dc98a8489ad5f0fc8615d
- Size of remote file:
- 711 MB
- SHA256:
- 31880861bcdc132a29064b4a29f04220656c5900830da9b234d99d7d23d7d8b8
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