Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_227 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_227 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_227")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_227") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_227", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1421831c18286d69cfe433a6ef85eee45c895a5849af713ff441c1999ea1791e
- Size of remote file:
- 2.24 GB
- SHA256:
- 43d63c8312ebce4e7aef94dc0c65bd76d75d0a934ce332ae2e36e89c167cf345
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