Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_121 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_121 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_121")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_121") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_121", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4192d28f818a87cbb3784f351d3bbe8c05011afde5897491339f8072103930b2
- Size of remote file:
- 2.24 GB
- SHA256:
- 4c45ca7bb34c57a1bc0366424e2e014c74040181b1bdb6619065361f0c61e8e2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.