Instructions to use AnonymousCS/populism_classifier_bsample_296 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_296 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_296")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_296") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_296", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2d0f1664f8086981f851a4262d05d1bb9c956355cd931828bba277a9359d583
- Size of remote file:
- 5.43 kB
- SHA256:
- 255326473b2ece676f8b3d18292a571edb1686fa41f39b5e2c2421e48a8a36bd
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