Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_250 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_250 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_250")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_250") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_250", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 419e2ed7a6712c38d585651f6ca2499ede6973dfcd1aa07bf925ec2245672c0b
- Size of remote file:
- 499 MB
- SHA256:
- 38e84a35c79c2206669210bc9b680a0d1c4e04e37c996c7cfa9f57ea8e5de928
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