Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_235 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_235 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_235")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_235") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_235", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b42b8ee01a20e916ca899a3d73520893998aa2c422b4793ea68f61cf544f7611
- Size of remote file:
- 499 MB
- SHA256:
- b4a5ea581ca75ad6dc993abb5b0a3988e3280ee353ec6bb3ce0f6a819976dd7e
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