Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_260 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_260 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_260")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_260") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_260", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d9fb6eb5f5276adbd1bf1f8a547432eda4bd4192c238c64df0ddaf98d00f1c8
- Size of remote file:
- 5.43 kB
- SHA256:
- f2bcdc457b9de3208203c1adfd0725e9b1b9d32f33827b08bfc2bed35e780d78
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