Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_255 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_255 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_255")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_255") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_255", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c7e59cee11fe6f87554e9f884488ef3e55c62861d576c8886c961687b9ba315
- Size of remote file:
- 5.43 kB
- SHA256:
- 4823050869bf4a8c577e2572508a3c195b316c56a7faa51bbd61d3f7de1cf158
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