Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_093 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_093 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_093")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_093") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_093", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78c0b5c41bb1202ac84a53c1ba0d6953fde0c0e13fbc21a66a5fefd155f85adf
- Size of remote file:
- 5.43 kB
- SHA256:
- 5eaaff4fa1e41a4ab8d5e873a3bd2c2083a553fa5cd57a32917702acd96b0c7f
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