Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_230 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_230 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_230")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_230") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_230", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8726b90a0d7b8a4f91b709a647337165b601f22fe5963b818ee250a06c949cb0
- Size of remote file:
- 2.24 GB
- SHA256:
- 76eb8753e2612c311ed031afdacc1fec00cbea5ec659696b8522d212d013fe5a
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