Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_197 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_197 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_197")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_197") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_197", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d15166af5f6e03f33fc0dfccc58df695614ee172730349180640fcc3e0512b9
- Size of remote file:
- 5.43 kB
- SHA256:
- ad0360fdb9eff9716080a66af7167b52a37d67136c10ec13a927f4e2754a5f6d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.