Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_193 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_193 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_193")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_193") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_193", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da63b9c37f63b2fb1878a9514177b594ea37f449f92a7abb42a7c18792671841
- Size of remote file:
- 1.11 GB
- SHA256:
- 1dff24f3a81907ee6684d6d065a92350d2cb9bc26ec7026d2f13a7df04366d68
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