Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_101 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_101")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_101") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_101", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb369fed3d2f4815f0c3f6432faf869176643d78350f9645c3306438cfd68d31
- Size of remote file:
- 1.11 GB
- SHA256:
- be9785bb3b042491a8cc3e10c2c853ea042b2cad56b3c0abe36b8b1690102961
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