Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_203 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_203 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_203")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_203") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_203", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94e6da65319163ce299e616a2d8219c40a1c85330b31bce9ebc28f04bd2950b9
- Size of remote file:
- 1.11 GB
- SHA256:
- c62790e4c03ca8812fe7085651561c9cf59819b9f72d756eb5cd8b95832a6959
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