Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_207 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_207 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_207")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_207") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_207", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea9f54f90740f7c84f1dbe15ecf1d007e21fc1f6f5b22c52d62025a7504caa14
- Size of remote file:
- 1.11 GB
- SHA256:
- 99ca9df5bb5c8e110ed519a6df24c4abcec0ac96ab93aa91dfcb2b5d76afb23e
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