Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_103 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_103 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_103")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_103") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_103", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7308fcbdf1a9406a4751d1b4d14787af55e2a091908e57cad60565e8cd4da5cd
- Size of remote file:
- 5.43 kB
- SHA256:
- 68a0f89bb881bf7594e55cdf9d6bc5eb194167cea6773da9e4ef2f1d707ac0b4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.