Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_250 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_250 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_250")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_250") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_250", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0276e53fedcf542a0e7b87f7808fb2fc7266a30d2619d7b1fd1f7bb286adbd53
- Size of remote file:
- 5.43 kB
- SHA256:
- f92d6018a97ae1045136f71df805f6d3688ef8cbe8e3b6b8abb4e0e7b1f39331
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