Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_253 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_253 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_253")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_253") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_253", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5f27eb7e956e582541dfd4a35cf22d911baed7d31c1b3c362637e769580ba96
- Size of remote file:
- 5.43 kB
- SHA256:
- b17621752fb51f4eb0d51926e980eb41e79c95525e1196ef711c209b99354cb4
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