Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_130 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_130 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_130")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_130") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_130", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d09ccbc9492ad4fe568c526ec4542ddd78602e170e76b737693b8b3c486a0639
- Size of remote file:
- 5.43 kB
- SHA256:
- 941134fce5b2c3a4a17e47d4b872962a6932c667d99e2419321a8381bb285f8f
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