Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_253 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_253 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_253")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_253") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_253", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d17d97123e6438cb661a34b5755ae181b9f90c75d471210ee1dd6a06480612b
- Size of remote file:
- 5.43 kB
- SHA256:
- 9d92b3f8141269823edd9df3ac3aa05dcd6633439a920250869b20ecbc3bb55f
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