Instructions to use AnonymousCS/populism_classifier_bsample_290 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_290 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_290")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_290") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_290", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7c9e15a5fada1e436b5e97d4b1970d4fd01a6ffa8593598e2c3aa32e12ecde2
- Size of remote file:
- 433 MB
- SHA256:
- e4a6d3532cd262c11e13eee70c0e12b941ab3deac7985c72cd08b29a58d2cdd8
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