Instructions to use AnonymousCS/populism_classifier_bsample_330 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_330 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_330")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_330") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_330", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af61359cb76b6f50698530d8c8d9e6d4e0c098867e7e9cf1fbc585bf51e8a4f9
- Size of remote file:
- 5.43 kB
- SHA256:
- 67ebc3e60b87f4aad606fd6f60b062b27f8c44d184ba48eb2e8059d192d77f49
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