Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_213 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_213 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_213")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_213") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_213", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a57488a8e120908610d3c3d7236e757cfe062eb1e4c37e62124a05457f27514
- Size of remote file:
- 2.24 GB
- SHA256:
- 60df7fa3a871df035ef6521e5b1545dc8ace39c6963f79f41f74cf6c163da1de
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