Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_260 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_260 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_260")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_260") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_260", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c0704fd7834366ac5d9b387fa2c8121878e5fc2830094c7b037d7f9e8a63cc4
- Size of remote file:
- 499 MB
- SHA256:
- 113207e08da6a2609a2606c504e01e608b783363bb3e15c21786a9c7a1efead6
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