Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_243 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_243 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_243")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_243") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_243", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88160fae1a9675dd956dc2aca5ebd27583ce23b5c9790559e5b563ef837775ca
- Size of remote file:
- 5.43 kB
- SHA256:
- 588403e50783f7ae0a8d63122c6b14156a5e59ece9aadb6ce19f3dcb4c632c94
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