Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_257 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_257 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_257")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_257") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_257", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48149aa33938271571fca0c159995e9d9685c4f520bdfa61bf0b96734fb37490
- Size of remote file:
- 5.43 kB
- SHA256:
- e08550cb9cdb47d923ca455ccc5ea9992070ff406cfc577c2dd554522051199a
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