Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_210 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_210 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_210")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_210") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_210", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e202949b10eabe81d41652458c5d024cd8f1898b031b24aa981f3eceb4531c8
- Size of remote file:
- 2.24 GB
- SHA256:
- 050034d335bb472adbd0dbf96c672f719e9b68561a0daa5b7b4ee3018159728e
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