Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_191 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_191 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_191")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_191") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_191", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cb073a149d24b032de5cd5937e57b5b464d3aa43342a6e620c3280a36d3c85d
- Size of remote file:
- 1.11 GB
- SHA256:
- 6992451b47a08f7d9e114b964bac9a17f13e02fa44e16fb414b068e0b1f97c6c
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