Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_243 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_243 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_243")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_243") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_243", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 215eb57930b948e012dbe8a71159e6e4482b8e7c0bf204b08600eeaa76c52c4f
- Size of remote file:
- 499 MB
- SHA256:
- b5e498687efe5c0210554997c47b9ba366dc8c2a6fb9c6900b6cb35c856b2191
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