Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_209 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_209 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_209")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_209") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_209", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a73f66844291fcea2874bcae0a1e36c4a805d8bf613629a3d68ba1654e38c97
- Size of remote file:
- 2.24 GB
- SHA256:
- 2f29149d482e488babc6e612b8bb6793d6ac44424e86969dbf7904e06c17dbcd
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