Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_251 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_251 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_251")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_251") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_251", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f628e555c801f8471a282104d45a6950714d2a50fac530fffa9b9221e53e3d94
- Size of remote file:
- 499 MB
- SHA256:
- 790936263473e597f29635fa6c61469ff7657802c6940b701310713cdbae616f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.