Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_200 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_200")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_200") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_200", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7783af6e8323ae31b7ac5477df32d2999ad676f8d49042d13024a296e14b7651
- Size of remote file:
- 1.11 GB
- SHA256:
- 5e6b435f8774b33da6069b0d5f30e730766e099911683cd95ca6b1d07add0114
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