Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_126 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_126 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_126")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_126") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_126", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2413acc12c0088e3090d1d3f40008101c29e635f9c242702ab2a43e83fd15a17
- Size of remote file:
- 2.24 GB
- SHA256:
- 10aa9692c30692fb0ce9a5021938459b1dc2fdc348c29259a30949506e8f7ceb
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