Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_259 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_259 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_259")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_259") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_259", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05eb446474d5024aae60f5416b2ee4030909371022eabfb8f1812840a7217ad7
- Size of remote file:
- 499 MB
- SHA256:
- d584c2482a6a6cf150e5d9394cb2a452e756d8cb0416ca86dca207888f041d1a
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