Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_080 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_080 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_080")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_080") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_080") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73211a56cd407f42edc4956b1e5566e27e1557ad212cad83e50717acb026cf37
- Size of remote file:
- 1.11 GB
- SHA256:
- c3cbf1ffa890021ee374d0175a0329d5fa2fd518805d62271fa26a38afadd3ae
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.