Instructions to use AnonymousCS/populism_classifier_bsample_005 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_005 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_005")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_005") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_005", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05645a7e3d92540f755e802189054ed5108d3b813025bb329c439120e15d15e8
- Size of remote file:
- 5.43 kB
- SHA256:
- 04c920b9f8fecb63eee74d1a46c2d639f7da507334c460986f891eb18a6eaa89
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