Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_093 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_093 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_093")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_093") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_093", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50027d0455a6b33c30a3e57f36f86aaf020a78b17fcf42c140ff3a44c66133b1
- Size of remote file:
- 1.11 GB
- SHA256:
- 394f000ca1befa2c5321836cf9c2a0bc2d21b2b6734ecdc60b1c065a9eec3ee1
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