Instructions to use AnonymousCS/populism_classifier_bsample_020 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_020 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_020")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_020") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_020", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7de47659784b8261751fb66cfb49ad51158a72eac8a0f157f7d8548521c6e4a
- Size of remote file:
- 711 MB
- SHA256:
- 037eb6ec4bc38d52e35931006f1c701e09f614a356b506aba865a4b373d4a03b
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