Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_233 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_233 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_233")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_233") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_233", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 751c412dcaeffc39576b122b52a5b0d02345c7737f3d9c5df5b6f620f382ac50
- Size of remote file:
- 2.24 GB
- SHA256:
- 64b740d89c670b1df920ad7f25e92b24404c7f21a580e6fd23a6f8e1ce84555a
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