Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_127 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_127 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_127")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_127") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_127", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d82e41d0b71473e958558a633b8d81f37e722d7bd9f04545b6d961ee3a5c933
- Size of remote file:
- 2.24 GB
- SHA256:
- 36e75200d4e00c75344685d3e35ba0c5253eda07e900d9fd560cf318e07cc691
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