Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_256")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_256") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_256", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 549eef83343075dd36bfb2529093e97d9e0acf85640f9d2bd5996ab3607be25e
- Size of remote file:
- 5.43 kB
- SHA256:
- 6a6f44bdc5a823ba56ea64d11a662b50d091f4bc1885cb623ffd22c7cf78d211
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