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:
- 82d7aa434e2b64530e4434248a1f5d7c10a786809bf9833139c352426bd147dc
- Size of remote file:
- 5.43 kB
- SHA256:
- c6e48c7e5de5f3fa0395ae846094ea4631c784e857f24e63f3121035473fcff1
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