Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_123 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_123 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_123")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_123") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_123", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8cd12c5bd06ba3849f740910b8c1221e19c65781c8e707fe50bb5dd2e7d32688
- Size of remote file:
- 5.43 kB
- SHA256:
- f1f27a17306641575c037b726f4b9e04c02920d0e56b7103d685a22c715b1597
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