Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_232 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_232 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_232")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_232") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_232", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 313d95a3ca934ba32559724fc49ccbde97d68504dfab93ff081827077dba4ae8
- Size of remote file:
- 2.24 GB
- SHA256:
- b34a07915ca2f97d8898ba6c7b948f2c48d5ffd10f08c56ead1754bf9ca521a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.