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:
- 86e234e9b72911285dd1cd03c39e3d9bad0dbb0e4051fa9d489233069bd8d8a0
- Size of remote file:
- 5.43 kB
- SHA256:
- 1e4f604587fd8e2bc96227bce957a28e1182a8fdc17f336fa1edea030ea11b87
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