Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_103 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_103 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_103")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_103") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_103", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 593394e9e5a9f5b27e2772f6dccc71a283032927a723b0e2205f1c520c1f3dac
- Size of remote file:
- 5.78 kB
- SHA256:
- d5a1ff68c71889c8bf80e98539b99d1b889964e426e3257e258b006a7f6ea8dc
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