Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_253 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_253 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_253")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_253") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_253", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c429da1e921dbd5bb88b27873ee354d8a5f6d2012d160f4e40fda10407f3f52
- Size of remote file:
- 499 MB
- SHA256:
- 5e3c1de9819936b8471cc0795e28568c55fa9c3222967059460053560b29ce69
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