Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_118 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_118 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_118")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_118") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_118", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 237e6b9e1fe2cf600e470f233652280613fcb6886b6a0cfc4be8229d156cbbcc
- Size of remote file:
- 2.24 GB
- SHA256:
- dfb8673c81e97d25b4bdd4bfea86b697ff5c3d9e4f35e219736217ae4573f20c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.